AIToday
Large Language ModelsOpen-Source AIAI Business & IndustryTHE DECODERPublished: Jul 17, 2026, 06:00 JST

Kimi K3 open model matches GPT-5.6 Sol, Claude Fable 5 in benchmarks; China AI prices rise

Kimi K3 open model matches GPT-5.6 Sol, Claude Fable 5 in benchmarks; China AI prices rise

3 Key Points

  1. What happened

    Kimi launched K3, a 2.8 trillion parameter open model with a one million token context window. In Kimi's benchmarks, K3 trails only Claude Fable 5 and GPT-5.6 Sol but beats all other tested systems including Claude Opus and Chinese rival GLM-5.2. Independent testing by Artificial Analysis scores K3 at 57 on the Artificial Analysis Intelligence Index, placing it fourth behind Fable 5 (60), GPT-5.6 Sol (59), and Opus 4.8 (56). Full model weights are scheduled for release by July 27.

  2. Why it matters

    K3 signals the end of ultra-cheap Chinese AI. Kimi's pricing—$0.30 per million input tokens (with cache hit) and $15.00 for output—is nearly 19 times higher than its predecessor K2.6 ($0.16 input, $4.00 output). Chinese providers overall are raising prices for frontier models. At $0.94 per task, K3 lands in the same range as GPT-5.6 Sol ($1.04) but costs roughly half of Claude Opus 4.8 ($1.80), positioning it as a competitive midrange option rather than a price-leader.

  3. What to watch

    K3 shows higher hallucination (51 percent) than its accuracy improvement (46 percent, up from 33 percent on the AA-Omniscience Index), and it uses a mixture-of-experts architecture activating only 16 of 896 experts. The model is available now via Kimi.com, mobile apps, and Kimi Code; a planned Kimi Hosted Agent platform with isolated environments for long-running tasks is in waitlist signup.

Not sure about something? Ask the AI

Questions and answers are published on this page.

Summaries like this, in your inbox every morning.

Context & Analysis

Kimi K3 represents a significant shift in Chinese AI economics. While the model delivers performance competitive with top-tier Western proprietary systems, its pricing strategy breaks sharply with the race-to-the-bottom dynamic that characterized Chinese AI for the past year. At $0.30–$3.00 per million input tokens and $15.00 per output, K3 is priced to compete with Claude Sonnet 5 (identical pricing) and sit between GPT-5.6 Sol ($0.50–$5.00) and open-weight competitors like DeepSeek V4 Pro ($0.04). This pricing reflects both the computational cost of training and serving a 2.8 trillion parameter model and a broader market signal: frontier AI models—whether proprietary or open-weight—are no longer treated as loss-leader commodities.

The performance data underscore K3's position in the upper midrange. Artificial Analysis's independent testing places K3 at 57 on the Intelligence Index, a clear fourth place, but the margin matters: it trails Opus 4.8 by only one point, and on agentic tasks (Elo 1,668), it substantially beats both Opus 4.8 and GPT-5.5. Kimi's own benchmarks show K3 winning roughly one-sixth of tests across a 35-test suite and placing second or third in most others. However, Artificial Analysis flags a troubling trade-off: K3's hallucination rate climbed to 51 percent even as accuracy improved to 46 percent, a 12-point jump from K2.6, suggesting the model generates more plausible-sounding but false outputs.

The open-weights release by July 27 will test whether market demand supports non-cheap open models. K3's efficiency gains—a mixture-of-experts design activating only 16 of 896 experts, and a new Kimi Delta Attention architecture enabling 6.3× faster decoding on million-token contexts—suggest the model was engineered for cost-effective inference at scale, not merely raw capability. For businesses running agentic workloads, the positioning as a platform for "Vision in the Loop" code generation and long-horizon task completion signals Kimi's intent to compete on developer utility rather than price, a marked departure from the commodity positioning of earlier Chinese models.

FAQ
How does K3 perform compared to other models?
On Artificial Analysis's Intelligence Index, K3 scores 57, placing fourth overall behind Claude Fable 5 (60), GPT-5.6 Sol (59), and Claude Opus 4.8 (56). On agentic tasks, K3 reaches an Elo rating of 1,668, beating GLM-5.2 (1,514), GPT-5.5 (1,494), and Claude Opus 4.8 (1,600), though falling short of Claude Fable 5 (1,760).
When will the open weights be available?
Full model weights are scheduled for release by July 27. K3 is already available now through Kimi.com, mobile apps (iOS, Android, HarmonyOS), Kimi Work desktop client, and OpenRouter.
How much does K3 cost?
One million input tokens cost $0.30 with a cache hit and $3.00 without; one million output tokens (including reasoning) cost $15.00. This is roughly 19 times higher than K2.6, which cost $0.16 per million input tokens (with cache hit) and $4.00 for output.
What is K3 designed to do?
K3 targets long-running software development with minimal human oversight, analyzing large codebases, coordinating terminal tools, and staying focused across many work steps. It uses a 'Vision in the Loop' system that examines screen captures, modifies code, and checks visible output.

AI news that matters for your work, delivered every morning.

Pick your industry and the AI tools you use, and get news related to your work every day.

Free · 30 seconds with Google · unsubscribe anytimeWhat is AIToday? →

Ask AI

Ask AI anything about this article. The AI reads this article, earlier AIToday articles, and Wikipedia, and cites its sources. Q&As are published on this page for other readers too.

Questions and answers are published on this page.

Related Articles

Next articleBuffett backs Google's $185B AI bet, calls race 'a game they don't want to play'