Kimi AI vs DeepSeek vs ChatGPT: 3 Picks for Canada [2026] -insider.org

What Changed in the Last Three Weeks

October 2026 moved quickly for all 3 suppliers. A timeline assists, due to the fact that the items overlap in time and the release dates in secondary protection frequently disagree by a day.

• October 7: OpenAI presented GPT-6 in ChatGPT with a function it calls Intelligent UI, which lets responses consist of interactive pieces such as diagrams, calculators and expense splitters. It reached Free and Go users the next day.
• October 17: DeepSeek updated its V4.1 Flash line to the 1017 variation, kept the API alias at deepseek-flash, and opened Search and Fetch APIs to outdoors designers.
• October 24: Moonshot revealed Kimi K3.1 Pro and a much faster Highspeed version, both readily available through Kimi apps and the API.
• October 26: OpenAI started rolling GPT-6.1 Terra into ChatGPT Work and Codex.
• October 29: OpenAI apparently included a US$ 500 Pro tier and resumed brand-new sign-ups on its US$ 200 Pro strategy.
• October 30: OpenAI stated it was upgrading GPT-6 in ChatGPT to offer much shorter responses and cut flattery.
• November 1: DeepSeek’s server-side Search and Fetch calls through its Harness, Claude Code and Codex stopped being totally free. Moonshot apparently closed Kimi K2 to brand-new API sign-ups the exact same day.
• November 4: Moonshot’s guaranteed date for the Kimi K3.1 Pro weights.

2 things stick out. Every supplier delivered a design or prices modification inside a single month, so any evaluation older than a couple of weeks explains a various item. Second, the design names keep increasing. OpenAI alone now notes GPT-6 Sol, GPT-6 Luna, GPT-6 Astra and GPT-6.1 Terra, and our earlier take a look at Gemini 4 Carbon versus GPT-6.1 Terra and DeepSeek V4.1 Flash currently required a glossary to keep them directly.

A calling note on DeepSeek. Our research study discovered no main indication of a different flagship called DeepSeek V4.1. The most recent verified release is DeepSeek-V4.1- Flash, upgraded to the 1017 variation, and the older V4-Pro API service remained readily available after a prepared shutdown was dropped. Throughout this post, DeepSeek V4.1 suggests the V4.1 Flash line unless we state otherwise.

How We Built This Comparison and What We Could Not Confirm

The approach is basic. We pulled recency-filtered research study on November 4, 2026, ran it through a current-facts inspect, and arranged every claim by how well it held up. A lot of products landed in a single-source container, implying one report or one scraped page backs them. A couple of were marked as reports. None were validated on both a brought supplier page and the research study feed. That forms how we compose. Realities get a called source or a hedge, and anything we can not support stays out of the tables.

The table listed below programs where the proof bases on the concerns Canadian purchasers ask a lot of. Read it as a map of spaces. If a row states not verified, the sincere relocation is to ask the supplier, not to presume the response.

We likewise attempted to scrape 2 completing contrast pages for structure criteria, and the scraper returned no functional text. We set our own bar: a longer, more structured treatment than the normal vendor-versus-vendor post, with an approach you can rerun yourself.

Kimi AI and K3.1 Pro: What Moonshot Shipped

Kimi K3.1 Pro is Moonshot’s existing flagship. Moonshot explains it as a design in the approximately 3-trillion-parameter class with a 1-million-token context window and native visual understanding. The business places it for coding, 3D development, monetary research study and long-horizon representative jobs. The Kimi API quickstart lists the design identifier as kimi-k3.1- professional and states gain access to follows an effective account top-up of a minimum of US$ 1, with top-up overalls setting rate limitations and concurrency.

It beings in a lineup. Kimi’s rates user interface on November 3 noted K3.1 Pro, K3.1 Pro Highspeed and the earlier K3 side by side, so K3 is not retired. K3.1 Pro is referred to as a post-trained follower to K3, which Moonshot launched in July. For readers who followed our earlier Kimi K3 contrasts versus Claude Sonnet 5 and GPT-5.6 Sol, the dive to K3.1 Pro mainly includes speed choices and a tighter coding focus.

The Highspeed alternative

Moonshot launched K3.1 Pro Highspeed along with the basic design. Reports state it runs about 2 to 3 times much faster and costs approximately double per token, at US$ 4 per million input tokens and US$ 20 per million output tokens versus US$ 2 and US$ 10 for the basic design. It is apparently consisted of in Kimi Code Pro and greater subscriptions. Speed matters most for interactive coding, where a designer waits on every conclusion, and matters little for over night batch tasks.

The open-weight pledge and the cyber compromise

Moonshot calls K3.1 Pro open-weight and stated it would release the complete weights on November 4. Up until an outdated Moonshot statement verifies conclusion, explain that as a strategy. Moonshot likewise stated it got rid of cyber-related information from the training corpus and from its reinforcement-learning environments to cut offending hacking ability while keeping basic coding capability. Digital Trends covered that security relocationMoonshot reported an internal cyber benchmark rating of 81.0% for K3.1 Pro versus 90.5% for a comparable variation without the mitigations. That figure is the business’s own, so it is worthy of care.

For a Canadian security group, the cyber modification cuts both methods. A design with weaker offending ability is a smaller sized abuse danger. It might likewise be a weaker partner for genuine penetration screening and red-team work, so check it by yourself jobs before you dedicate.

DeepSeek V4.1 Flash: What the Label Really Means

DeepSeek’s latest validated release is DeepSeek-V4.1- Flash, which initially appeared on September 10 with native multimodal assistance and after that got the 1017 upgrade on October 17. The business’s website stated the upgrade brought much faster, lower-cost project-development ability, and its API changelog stated rates remained the same after the upgrade. The API alias is deepseek-flash, which constantly routes to the current Flash variation. That alias style comes in handy, since your code never ever requires a model-name modification. It likewise indicates the design behind your calls can move without a code diff.

Protection of DeepSeek’s V4.1 Flash upgrade and Search API launch from Asia Daily matches the changelog on the bottom lines. DeepSeek opened Search and Fetch APIs to outdoors designers, noted at US$ 0.75 per 1,000 effective demands each. Server-side calls through DeepSeek Harness, Claude Code or Codex were totally free up until November 1, Beijing time, and billing started after that. If you developed a representative that leans on web retrieval throughout the complimentary window, examine your costs today.

Design retirements are worthy of attention too. Secondary reports state the older V4 Flash identifiers were retired or rerouted to V4.1 Flash, which demands to deepseek-v4-pro were routed to V4.1 Flash for a while before DeepSeek stated it would keep using V4 Pro. Those reports dispute on information, so confirm your own design routing in the API reaction metadata rather of relying on an alias.

DeepSeek likewise rearranged in mid-October. It combined its Agent Harness, Web, App and Platform groups into one Product Department, and a Lookonchain report names Cui Tianyi as its head. We note that as a single-source report. Our research study discovered no existing authorities titles for DeepSeek’s other executives, so we call none.

ChatGPT in the GPT-6 Era: Which Model You Actually Get

ChatGPT is hardest to select due to the fact that the response to which design am I utilizing depends upon your strategy. OpenAI’s release notes, as obtained for this research study on October 31, state Plus, Pro, Business and Enterprise utilize GPT-6 Sol, while Free and Go usage GPT-6 Luna. Pro thinking works on GPT-6 Astra, and GPT-6 Pro, powered by Astra, is reported as offered to the Pro tiers, Business and Enterprise users. GPT-6.1 Terra, a quick design focused on high-volume expert deal with image analysis and computer system usage, started presenting to Work and Codex on October 26. Another specific design, GPT-6 Rosalind Research, began a restricted rollout to authorized Business consumers for life-sciences deal with October 30.

A few of our research study lines dispute on which Luna generation serves the totally free tier, with one line indicating an older GPT-5.6 Luna. We follow the release-notes line due to the fact that it brings the later date. In any case, the totally free tier gets a lighter design than the paid tiers.

On cost, OpenAI’s aid center apparently notes Plus at US$ 20 a month and 3 Pro tiers at US$ 100, US$ 200 and US$ 500 a month. The US$ 500 tier supposedly consists of Ultrafast variations of GPT-6 Astra and GPT-6.1 Sol. ChatGPT Business seats apparently run US$ 25 per user monthly billed monthly, or US$ 20 billed each year, with premium seats at US$ 125 and US$ 100. The main rates page we recovered revealed Brazilian-real rates, which informs us absolutely nothing about Canada. Our guide to ChatGPT Go, Plus and Pro in Canada covers the strategy ladder in more depth, and you need to inspect the rates page from a Canadian IP address before you spending plan.

Beyond the chat window, OpenAI is presenting GPT-6 to qualified Pro, Plus, Enterprise and Business users since November 3. That makes ChatGPT the more completed customer item, even where its raw design ratings track. Readers who mainly desire live web responses need to likewise read our AI search contrast of Perplexity, ChatGPT and Gemini.

Specifications Side by Side

The table listed below compares the 3 on item structure. Numerical specifications such as context windows and specification counts being in the prose above, where we can connect a source and a hedge to each.

The pattern is clear enough. ChatGPT wins on item polish, Kimi on context size and open-weight aspiration, and DeepSeek on the expense of raw tokens. None of the 3 releases a Canadian-dollar rate or a Canadian residency guarantee that our research study might validate.

Criteria: Three Sources and Where They Disagree

Criteria are where this contrast runs thinnest, so here is precisely what exists. We discovered 3 type of proof, and none is a tidy head-to-head test of all 3 items.

id=”toc-9″> Source one: the Artificial Analysis Intelligence Index

On October 29, a Chinese federal government science-and-technology news outlet reported that K3.1 Pro ranked 4th on the Artificial Analysis Intelligence Index with a rating of 55, up 11 points from its predecessor. A different, lower-confidence report declares a later index modification put the design ninth with a rating of 46. We deal with the modification as a report up until Artificial Analysis releases it. Both reports explain a ranking, not a three-way contest with DeepSeek and ChatGPT, so neither shows total supremacy.

Source 2: Moonshot’s own tests

Moonshot’s internal cyber standard, covered previously, is the supplier’s own number. Our research study discovered no vendor-published coding rating we might verify, so we leave coding leaderboards out. Vendor-run tests tend to flatter the supplier, and a harness setting can swing a coding rating by a number of points.

Source 3: third-party claims versus competitors

Reports state K3.1 Pro gone beyond or ranked ahead of DeepSeek V4.1-Flash-1017 and OpenAI’s GPT-6 Astra on particular third-party examinations. The phrasing is loose, and it does not call the tests. A VentureBeat report on the design’s open-weights standing brings accusations of a paid influencer project around the launch, and a DEV Community post makes a comparable claim. We can not evaluate those claims. They are a factor to wait on independent outcomes before you accept any launch-week leaderboard.

The takeaway: Kimi K3.1 Pro looks competitive on reported third-party rankings, however a fourth-place index outcome and a vendor-run rating are not a decision. Run the little test in the migration area and put your own jobs on the scoreboard.

A couple of practices assist when you check out any leaderboard this month. Examine the date, since index approaches get modified, as the reported Artificial Analysis modification programs. Examine who ran the test, because a vendor-run rating and an independent rating response various concerns. Examine which variation was evaluated, since Highspeed, basic and Flash constructs can act in a different way. And inspect whether the test resembles your work. A design that tops a coding index might still discover your invoice-parsing triggers or your French-language assistance tickets, which is why a little golden set of your own beats any public table.

Prices: API Rates, Plans and the Canadian Dollar Problem

Start with the structure, then the reported numbers. The table covers how each supplier charges. The figures follow in prose, each connected to its source.

Kimi. API rates for K3.1 Pro were reported at US$ 2 per million input tokens, US$ 0.20 per million cached-input tokens and US$ 10 per million output tokens. In China, Caixin reported lower yuan rates, and Kimi’s China prices user interface revealed greater yuan figures for the Highspeed version. For customers, Kimi’s US-dollar page on November 3 revealed annual-billing equivalents of US$ 15 for Plus, US$ 31 for Pro, US$ 79 for Max and US$ 159 for Ultra each month, versus routine month-to-month rates of US$ 19, US$ 39, US$ 99 and US$ 199. The page did not explain whether any of it appears in Canadian dollars.

DeepSeek. The main platform page, upgraded October 2, noted DeepSeek-V4-Flash at US$ 0.0028 per million cached-input tokens, US$ 0.14 per million uncached-input tokens and US$ 0.28 per million output tokens, and V4-Pro at US$ 0.003625, US$ 0.435 and US$ 0.87. The changelog stated costs fell with the V4.1 Flash release, however we might not recover the complete table. Secondary trackers list V4.1 Flash at peak rates of US$ 0.006, US$ 0.30 and US$ 1.20, with rates cut in half off-peak. Those trackers disagree with each other, so utilize the conservative reading and validate in the platform console.

OpenAI. A business rate card apparently notes GPT-6 Pro (Astra) at US$ 10 per million input tokens and US$ 50 per million output tokens, and GPT-6 Sol at US$ 2 and US$ 10. Another line puts GPT-6 Luna at US$ 0.10 and US$ 0.50. A 3rd line states OpenAI considerably cut Sol and Luna API costs on November 2, so the Sol and Luna figures here might currently be stagnant. The rate card itself transferred to token-based rates for Enterprise on November 4.

A worked example

Compare the noted per-million-token rates instead of a fabricated work. Kimi K3.1 Pro is noted at US$ 2 for input and US$ 10 for output, with cached input at US$ 0.20. GPT-6 Sol is noted at the exact same US$ 2 input and US$ 10 output on the rate card. DeepSeek-V4.1- Flash is reported at US$ 0.30 input and US$ 1.20 output at peak hours, with half-price off-peak rates. The rates might have moved, so examine each supplier’s page before budgeting. DeepSeek is the most inexpensive by a large margin. Our earlier cost-gap breakdown of Claude Fable 5.1, GPT-5.6 Sol and Gemini 3.8 Flash revealed the exact same spread throughout suppliers.

Canadians deal with 2 additional expenses that none of these pages explain. Billing in United States dollars exposes you to the currency exchange rate, and a card from a Canadian bank might include a foreign-transaction cost. Include GST or HST to your budget plan if the supplier charges it, due to the fact that the pointed out pages did not state.

Canadian Privacy, Data Residency and Compliance

Rate is just half the Canadian concern. The other half is where your triggers go. None of the 3 suppliers has a Canadian residency dedication that our research study might validate, which matters for anybody dealing with individual details under PIPEDA or, in Quebec, under Law 25. This area is analysis, illegal suggestions.

Start with the structural distinction. A hosted Kimi or DeepSeek service sends your timely to the supplier’s servers, and the sources we saw explain prices pages in yuan for China-based operations. Moonshot and DeepSeek are both Chinese business, so a Canadian company ought to ask where the reasoning runs, which entity holds the information, and what the supplier’s retention terms state. OpenAI is a United States business and the very same concerns use, though lots of Canadian companies currently hold business arrangements with United States suppliers and understand the drill.

Open weights alter the image, if they get here. A downloadable design can work on hardware you manage, in a Canadian information centre or on a server in your workplace, and no timely leaves your network. That is the greatest personal privacy argument for Kimi, and the one to view after today’s assured drop. A design near the 3-trillion-parameter class is not a laptop computer task. Anticipate to require rack-scale hardware or a Canadian cloud service provider that hosts open weights, and anticipate the licence terms to matter if you prepare to resell gain access to.

For a useful list, ask each supplier these 5 concerns in writing:

1. Where do you procedure and shop triggers and outputs for my account, by nation?
2. Do you train on my information by default, and how do I pull out?
3. What is the retention duration for chat history and API logs?
4. Which subprocessors can touch my information, and where are they found?
5. Will you sign an information processing contract that shows Canadian personal privacy law?

A tidy composed response from your supplier today deserves more than a guarantee on a marketing page. Our AI and artificial intelligence protection tracks supplier policy modifications as they land.

5 Real-World Uses the Vendors Point To

We have no hands-on test results for these designs, so these 5 examples originated from functions the suppliers and press explain. Each is hedged appropriately.

1. Long-horizon coding with Kimi Code. Moonshot ships Kimi Code as an item, and Kimi’s own page states K3 gain access to starts at the Plus strategy and greater. The Highspeed design is supposedly consisted of from Pro up. A group refactoring a big repository advantages most from the million-token window, because the design can hold much more of the code in one pass.

2. Financial research study on Kimi. Moonshot lists monetary research study and monetary modeling amongst K3.1 Pro’s strengths. A Canadian expert summing up long filings might discover the long context beneficial, though anything touching customer information requires the personal privacy concerns from the previous area addressed.

3. Web-grounded representatives on DeepSeek. With Search and Fetch APIs priced at US$ 0.75 per 1,000 effective demands each, a designer can construct a retrieval representative without a different search supplier. The November 1 billing modification indicates the complimentary trip ended, so cost the search calls into your strategy.

4. Interactive responses in ChatGPT. Smart UI lets a reply consist of a calculator, a diagram or a costs splitter. A small-business owner splitting a shared expenditure or a trainee resolving a physics diagram gets a tool, not a wall of text. That is a customer function the other 2 do not match in our research study.

5. Life-sciences research study with GPT-6 Rosalind Research. OpenAI started a restricted rollout of this design to authorized Business consumers on October 30. Gain access to is gated, so most Canadian laboratories can not utilize it yet, however it reveals OpenAI selling specialized designs inside the strategy structure.

A 6th case worth a line: voice. ChatGPT Voice works on GPT-Live-1.1 and the smaller sized Quip version, and neither competitor reveals a voice item in our research study. If hands-free usage matters to you, that settles the option. Groups comparing assistants for workplace work must likewise read our take a look at Copilot, ChatGPT and Gemini for Canadian groups, which covers the seat-licence side that this piece avoids.

Use-Case Recommendations

The table matches typical requirements to a choice. The thinking originates from item structure and the hedged realities above, not from a head-to-head trial.

Combined setups frequently beat a single option. A typical pattern is an inexpensive design for bulk work and a more powerful one for the tough cases, with a router in front. Another is ChatGPT for personnel who desire an ended up item and a Kimi or DeepSeek API for designers who desire control of expense. Our rate contrast of GPT-6 Astra, Claude Fable 5.1 and Gemini 3.8 Flash makes the exact same point about tiering by expense.

Migration Guide: Moving Between Kimi, DeepSeek and ChatGPT

Changing suppliers expenses less than it utilized to, since lots of suppliers use API paths formed like OpenAI’s. Examine each supplier’s paperwork to validate this before you depend on it. The actions listed below work whichever instructions you move.

1. Inventory your triggers. List every system timely, tool meaning and output format your app depends upon. Covert reliances, such as one design’s routine of returning a specific JSON shape, trigger a lot of migration bugs.
2. Construct a golden set. Pull 30 to 50 genuine jobs from production, with the responses you accepted. Genuine jobs beat a public leaderboard for your usage.
3. Parameterize the endpoint. Move base URL, secret and design name into environment variables so one script can strike any supplier.
4. Run the golden set on all 3. Tape precision, latency and token counts for each call.
5. Expense it from your own tokens. Increase your determined input and output tokens by the rates in your supplier console, not by a tracker’s rates.
6. Test context limitations. If you prepare to lean on a million-token window, load a genuine long file and examine recall at the back of it.
7. Examine failure behaviour. Force rate-limit mistakes and malformed inputs. Verify your retry reasoning deals with each supplier’s mistake format.
8. Run both in parallel. Send out a piece of live traffic to the brand-new design and compare outcomes for a week before you cut over.
9. Pin what you can. If a supplier provides outdated design variations, pin one. With rolling aliases like deepseek-flash, log the design field in each reaction so you can find a quiet modification.

This script offers you a repeatable latency and token check. It presumes each supplier exposes a chat conclusions path that accepts the typical message format, so verify that in the docs. Set the base URLs, secrets and design names in your shell.

import json, os, time, data, urllib.request TARGETS=
    "kimi": ("KIMI_BASE_URL" "KIMI_API_KEY" "kimi-k3.1-pro"
    "deepseek": ("DEEPSEEK_BASE_URL" "DEEPSEEK_API_KEY" "deepseek-flash"
    "openai": ("OPENAI_BASE_URL" "OPENAI_API_KEY"os.environ.get("OPENAI_MODEL" ""), PROMPTS=def call( base, secret, design, timely): body=json.dumps( ). encode() req=urllib.request.Request( base.rstrip("/"+ "/chat/completions"information=body, headers=,) start=time.time() with urllib.request.urlopen( req, timeout=120) as resp: information=json.load( resp) return time.time() - begin, information for name, (base_env, key_env, design) in TARGETS.items(): base, secret=os.environ.get( base_env), os.environ.get( key_env) if not base or not essential or not design: print( name, "skipped, missing env vars"continue times, tokens_in, tokens_out=[]0, 0 for product in PROMPTS: secs, information=call( base, secret, design, product["prompt"]use=data.get("usage") times.append( secs) tokens_in +=usage.get("prompt_tokens"0). tokens_out +=usage.get("completion_tokens"0) print(name, "served by"data.get(
        "model") print(name, "median seconds"round(statistics.median(times), 2),
          "input tokens"tokens_in, "output tokens"tokens_out)

Feed the token overalls into the rate formula for each supplier and you get an expense for your work, not a guess. Printing the design field from each reaction likewise reveals you which design in fact responded to, which matters with rolling aliases.

Advantages and disadvantages

The cons column brings a pattern worth mentioning clearly. Every item does not have something a Canadian purchaser requirements, and the space is the very same for all 3: a validated Canadian-dollar rate and a residency guarantee. Till one supplier fills it, the winner is whichever one responses your composed concerns best.

Decision: Which One Should a Canadian Pick

There is no single winner, and anybody who names one from launch-week information is thinking. Here is the call by purchaser type, backed by the proof we might put together.

Choose ChatGPT if you desire a completed item. It has the broadest customer functions, a totally free tier, voice, and called group seats. You pay more on top end, and you accept closed weights. For many people and little groups, that is the lowest-friction option.

Choose DeepSeek if token expense drives the choice. On every set of rates we discovered, it came out least expensive, by an order of magnitude versus the premium tiers. Log the design field, verify present rates in the console, and prepare for the moving alias.

Select Kimi K3.1 Pro if you deal with substantial contexts or desire self-hosting. The million-token window and the open-weight strategy are the genuine differentiators. Wait on the weights to land, await independent benchmark outcomes, and check out the licence before you construct an item on it.

Our total take, scored on proof quality: ChatGPT leads on validated item functions, DeepSeek leads on reported expense, and Kimi leads on capacity that still requires evidence. Review this contrast once the Kimi weights ship and Artificial Analysis settles its index. We will upgrade the numbers here when sources validate them.

3 advancements would alter that call. A verified Kimi weights launch with a liberal licence would make self-hosting a severe choice for Canadian companies with rigorous residency requirements. A released Canadian-dollar rate or a Canadian area from any supplier would reset the expense mathematics for everybody. And an independent, multi-vendor criteria that names its tests would change the loose third-party claims we have now. Look for those 3 signals over the next couple of weeks, due to the fact that every one moves the suggestion.

Regularly Asked Questions

What is Kimi AI?

Kimi AI is the assistant and design household from Moonshot AI. Its existing flagship is Kimi K3.1 Pro, obtainable through Kimi.com, mobile apps, Kimi Work, Kimi Code and the Kimi API.

Is Kimi K3.1 Pro much better than ChatGPT?

It depends upon the job. Reports state Kimi K3.1 Pro beat GPT-6 Astra on specific third-party tests, however those tests are unnamed and the index ranking was supposedly modified. ChatGPT uses more customer functions. Evaluate your own jobs before changing.

Are the Kimi K3.1 Pro weights offered to download?

Moonshot stated it would release the complete weights on November 4, 2026. We might not verify that the release occurred, so inspect Moonshot’s statements before preparing a self-hosted develop.

Is DeepSeek V4.1 a genuine design?

The verified release is DeepSeek-V4.1-Flash, upgraded to the 1017 variation on October 17. We discovered no main indication of a different V4.1 flagship, so V4.1 is shorthand for the Flash line.

Which is most inexpensive for designers?

DeepSeek, on every rate set we discovered. Examine the platform console for existing figures, due to the fact that trackers disagree and the supplier stated costs fell with the V4.1 Flash release.

Do any of these deal Canadian-dollar prices or Canadian information residency?

Our research study might not validate either for any of the 3. Ask each supplier in composing, and deal with US-dollar rates as the standard till they state otherwise.

Can I change in between the 3 without rewording my app?

Frequently yes, if each supplier exposes an API path suitable with the typical chat format. Verify in the docs, parameterize the endpoint, and run a golden set of your own jobs before moving live traffic.