Released July 16, 2026; open weights July 26. Cache-hit input $0.30/1M. Subscriptions: Adagio (free) to Vivace $199/mo; full 1M context only on Allegro ($99) and up. New signups paused July 19 near GPU capacity, reopening in batches.
Open weights (July 26, 2026) — at 2.8T parameters, the largest open-weight release in history
Weaknesses
Most expensive Chinese-lab model ever ($3/$15) with always-on thinking driving high output-token burn and slow responses
2.8T size makes self-hosting impractical despite open weights; consumer signups were paused July 19 over GPU capacity
Real-world use cases
What people actually use Kimi K3 for.
Hardest reasoning tasks — #4 of all models on AA Intelligence Index v4.1 (57.1), ahead of Claude Opus 4.8
Agentic coding at 81.2 FrontierSWE and 88.3 Terminal-Bench 2.0 (Moonshot-reported)
1M-context research synthesis with always-on extended thinking
How Kimi K3 compares
The nearest models people weigh against it, and what actually separates them.
vs GPT-6 Astra — Against GPT-6 Astra (OpenAI), Kimi K3 runs about 70% cheaper per token and gives up 1.1x on context. Take Kimi K3 unless you specifically need what GPT-6 Astra does better.
vs Claude Fable 5.1 — Against Claude Fable 5.1 (Anthropic), Kimi K3 runs about 70% cheaper per token. Take Kimi K3 unless you specifically need what Claude Fable 5.1 does better.
vs Claude Fable 5 — Against Claude Fable 5 (Anthropic), Kimi K3 runs about 70% cheaper per token. Take Kimi K3 unless you specifically need what Claude Fable 5 does better.
Price History
Kimi K3 pricing over time
→0% since Aug 7
25 data points · tracked daily since Aug 7, 2026
Ready to try it?
Start using Kimi K3
Frontier-level reasoning and agentic coding. Start free — no card required.
OpenAI's September 3, 2026 frontier release — the first GPT-6 model and OpenAI's answer to Claude Fable 5.1 two days earlier. State of the art on computer use (OSWorld 2.0 72.6% in ~47% less time than GPT-5.6 Sol), agentic coding (Terminal-Bench 4.0 57.9%), and frontier math (FrontierMath Tier 4 97.6%). $10/$50 per 1M tokens, 1.05M context, 128K output, knowledge cutoff April 30, 2026.
Verdict
OpenAI's frontier answer to Fable 5.1 — computer-use and agentic-coding leader at $10/$50.
Quality score
99%
Pricing
$10.00/1M in
$50.00/1M out
Speed
Deliberate
2/5 speed
Context
1.1M tokens
Released September 3, 2026. API ID gpt-6-astra; rolling out over the coming days to ChatGPT Plus, Pro, Business and Enterprise (usage inside existing allowances; GPT-6 Astra Pro for Pro/Business/Enterprise; Enterprise off by default), the OpenAI API, Microsoft Azure and Amazon Bedrock. Standard API pricing $10/$50 per 1M tokens; Fast mode is up to 2x speed at 2x price; cache reads and writes have separate rates. Model docs list 1,050,000 context, 128,000 max output, knowledge cutoff April 30, 2026, reasoning efforts up to 'max'. Published launch numbers (Astra / GPT-5.6 Sol / Fable 5.1 / Opus 5): OSWorld 2.0 72.6 / 65.7 / — / 70.2; Terminal-Bench 4.0 57.9 / 37.3 / 55.8 / 52.3; Terminal-Bench Science 0.1 64.6 / 22.4 / 52.6 / 30.0; FrontierMath Tier 4 v2 97.6 / 83.0 / 87.8 / 73.2; GPQA Diamond 96.0 / 94.6 / 93.7 / 93.7; Humanity's Last Exam w/ tools 57.2 / — / 65.0 / 63.6; AutomationBench 41.4 / 18.1 / 31.4 / 26.9; DeepSWE v1.1 74.1 / 72.7 / 67.4 / 73.7; ARC-AGI-2 95.0 / 92.5 / 90.0 / 90.4; ARC-AGI-3 99.9 (OpenAI responses-API harness; ARC Prize's stateless runs score far lower) / 7.8 / — / 30.2; ExploitBench 100.0 / 78.5 / — / 70; SRE-Bench 88.0 / 55.9; Artificial Analysis Intelligence Index v4.1.1 61.2 / 60.9 / 65.7 / 63.1. Meets the Critical threshold for cybersecurity under OpenAI's Preparedness Framework; advanced cyber workflows gated behind OpenAI Daybreak. All figures from OpenAI's launch post and model docs, verified September 4, 2026.
Computer use leaderFrontierAgenticReasoningLong contextPremiumNew
Best for
Computer and browser use, long-horizon agentic coding, and frontier math and science work
Anthropic's September 1, 2026 frontier release and the new capability ceiling for coding, agents, and scientific work. Base pricing is unchanged at $10/$50, but cache reads dropped 75% to $0.25/1M — roughly 25% cheaper on typical workloads and up to 45% cheaper on agentic ones. 1M context, 128K output, adaptive thinking always on.
Verdict
New frontier leader — better than Fable 5 on every published benchmark, and cheaper to run.
Quality score
98%
Pricing
$10.00/1M in
$50.00/1M out
Speed
Deliberate
2/5 speed
Context
1M tokens
Released September 1, 2026 alongside Claude Mythos 5.1, the first update to the Mythos-class line since Fable 5 on June 9. API ID claude-fable-5-1; generally available on the Claude API, Amazon Bedrock, Google Cloud, and Microsoft Foundry. Published launch numbers (Fable 5.1 / Fable 5 / Opus 5 / GPT-5.6 Sol): Terminal-Bench-Science 0.1 52.6 / 24.7 / 29.0 / 22.4; Terminal-Bench 4.0 55.8 / 42.0 / 52.3 / 37.3; CursorBench 3.2.0 73.4 / 70.5 / 70.0 / 67.2; AutomationBench 31.4 / 17.1 / 26.9 / 19.6; OSWorld 2.0 strict 41.7 / 36.1 / 39.6; Humanity's Last Exam (no tools) 60.9 / 57.8 / 56.6; GDPval-AA v2 1853 / 1723 / 1824 / 1711. GDPval-AA v2 is rescaled from the v1 numbers quoted on the Fable 5 page and is not directly comparable to them.
Anthropic's new Mythos-class flagship and the most capable coding model anyone can use — 80.3% SWE-Bench Pro, an 11-point jump over Opus 4.8. 1M context, 128K output, native parallel subagents. Released June 9, 2026.
Verdict
Superseded by Fable 5.1 — still 80.3% SWE-Bench Pro, but 5.1 is better and cheaper to run.
Quality score
98%
Pricing
$10.00/1M in
$50.00/1M out
Speed
Deliberate
2/5 speed
Context
1M tokens
Launched June 9, 2026 as the public, Mythos-class release. Available on the Claude API, Microsoft Foundry, and Google Vertex AI. Free for all users until June 22, 2026. Same underlying model as Claude Mythos 5, with safeguards that block specific high-risk cyber responses. Superseded by Claude Fable 5.1 on September 1, 2026 — same $10/$50 base pricing, cache reads cut from $1.00 to $0.25 per 1M tokens.
SWE-Bench Pro 80.3%Mythos-classParallel subagentsAgenticLong contextPremiumSuperseded
Best for
The hardest coding tasks, autonomous multi-step agents, and frontier-grade reasoning
Kimi K3 costs $3 per million input tokens and $15 per million output tokens on the API, with cached input at $0.3 per million. A month of 10M input and 2M output tokens runs about $60.00 at list price, before any batch or caching discounts.
What is the context window of Kimi K3?
Kimi K3 has a 1M tokens context window, with up to 131k tokens of output per response. That is the total of prompt plus response the model can hold in one request.
What is Kimi K3 best for?
Kimi K3 is best for frontier-level reasoning and agentic coding. It is a strong fit when that workflow matters more than the tradeoffs around premium pricing and deliberate speed.
When should I avoid Kimi K3?
You need fast responses or predictable output costs — always-on thinking burns tokens.
What is a cheaper alternative to Kimi K3?
Grok 4.5 (xAI) at $2.00/1M/1M input against Kimi K3's $3.00/1M/1M — roughly 56% less per token all in. Best cost-per-solved-task coding agent — efficiency over ceiling. Compare it first if Kimi K3's pricing is the thing stopping you.
What is a faster alternative to Kimi K3?
GPT-6 Astra — deliberate against Kimi K3's deliberate, with 1.1M tokens of context. Worth the swap when response time is what your users notice rather than the last few points of reasoning depth.
Newsletter
Get notified when Kimi K3 pricing changes
We track pricing daily. When this model drops or spikes, you'll know first.
No spam. Useful updates only. Affiliate disclosures always clearly labeled.