Qwen3 235B-A22B Thinking 2507 vs Kimi K2 Thinking
Too close to call on our weighted score (Kimi K2 Thinking 56, Qwen3 235B-A22B Thinking 2507 55). The right pick depends on what you value most.
Alibaba (Qwen)Qwen3 235B-A22B Thinking 2507
55/100- ECI143.8
- Price$0.30 / $2.90
- Context262K
Moonshot AIKimi K2 Thinking
56/100- ECI145.9
- Price$0.60 / $2.50
- Context262K
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Make it a three-way comparison.
Too close to call
It is close. Our weighted score puts them within a point (Kimi K2 Thinking 56/100, Qwen3 235B-A22B Thinking 2507 55/100), so choose by what matters most for your work: Kimi K2 Thinking for raw capability and Qwen3 235B-A22B Thinking 2507 on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityKimi K2 ThinkingCapabilities Index (ECI): Kimi K2 Thinking 145.9 · Qwen3 235B-A22B Thinking 2507 143.8
- Lowest priceQwen3 235B-A22B Thinking 2507Qwen3 235B-A22B Thinking 2507 $0.95 · Kimi K2 Thinking $1.07 per 1M tokens (3:1 blend)
- Longest contextAbout the sameQwen3 235B-A22B Thinking 2507 262,144 · Kimi K2 Thinking 262,144 tokens
- Widest inputsSame inputsQwen3 235B-A22B Thinking 2507: Text · Kimi K2 Thinking: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Qwen3 235B-A22B Thinking 2507 | Kimi K2 Thinking |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 69 | 71 |
| Price | 25% | 49 | 46 |
| Inputs & features | 15% | 35 | 35 |
| Context window | 10% | 37 | 37 |
| Overall | 100% | 55/100 | 56/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Qwen3 235B-A22B Thinking 2507Alibaba (Qwen) | Kimi K2 ThinkingMoonshot AI |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 143.8 | 145.9 (best) |
| ECI rank | #93 of 165 | #84 of 165 (best) |
| GPQA DiamondGraduate-level science questions | 80.1% | 84.2% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 86.7% (best) | 83.1% |
| SimpleQA VerifiedShort factual questions | 40.4% | — |
| Price per million tokens | ||
| Input | $0.30 (best) | $0.60 |
| Output | $2.90 | $2.50 (best) |
| Cached input | — | — |
| Blended (3:1) | $0.95 (best) | $1.07 |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 11 providers | Median of 15 providers |
| Limits | ||
| Context window | 262,144 tokens | 262,144 tokens |
| Max output | 81,920 tokens | 262,144 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yes | Yes |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | OpenApache 2.0 | Open |
| API model ID | — | — |
| API providers | 12 | 16 (best) |
| Released | Jul 25, 2025 | Nov 6, 2025 |
| Knowledge cutoff | — | Aug 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Qwen3 235B-A22B Thinking 2507$8.80
- Kimi K2 Thinking$11.00
Which should you choose?
Which is better: Qwen3 235B-A22B Thinking 2507 or Kimi K2 Thinking?
It is close. Our weighted score puts them within a point (Kimi K2 Thinking 56/100, Qwen3 235B-A22B Thinking 2507 55/100), so choose by what matters most for your work: Kimi K2 Thinking for raw capability and Qwen3 235B-A22B Thinking 2507 on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Qwen3 235B-A22B Thinking 2507 or Kimi K2 Thinking?
Qwen3 235B-A22B Thinking 2507 is cheaper at $0.30 input / $2.90 output per million tokens (median across 11 API providers). Kimi K2 Thinking costs $0.60 input / $2.50 output per million tokens (median across 15 API providers). At a typical mix of three input tokens to one output token, that is $0.95 per million tokens for Qwen3 235B-A22B Thinking 2507 versus $1.07 for Kimi K2 Thinking (1.1× as much).
Which scores higher on benchmarks?
Kimi K2 Thinking scores higher on the Capabilities Index (ECI): Kimi K2 Thinking 145.9 (#84 of 165) and Qwen3 235B-A22B Thinking 2507 143.8 (#93 of 165). The confidence ranges of the top two overlap (143.3–147.4 vs 141.9–145.2), so treat the gap as small. On individual benchmarks: GPQA Diamond — Kimi K2 Thinking 84.2%, Qwen3 235B-A22B Thinking 2507 80.1%; OTIS Mock AIME 2024–2025 — Qwen3 235B-A22B Thinking 2507 86.7%, Kimi K2 Thinking 83.1%.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3 235B-A22B Thinking 2507 and Kimi K2 Thinking yet, so there is no like-for-like coding score. On overall capability, Kimi K2 Thinking leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.
Which has the bigger context window?
Qwen3 235B-A22B Thinking 2507 and Kimi K2 Thinking share the same 262,144-token context window. Maximum output per response: Qwen3 235B-A22B Thinking 2507 up to 81,920, Kimi K2 Thinking up to 262,144 tokens.
Which can read images, PDFs, audio or video?
Qwen3 235B-A22B Thinking 2507 accepts text; Kimi K2 Thinking accepts text. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights (Apache 2.0), so you can self-host them.
Which is newer?
Kimi K2 Thinking is the newest, released Nov 6, 2025. Qwen3 235B-A22B Thinking 2507 came out Jul 25, 2025. Knowledge cutoff: Kimi K2 Thinking Aug 2024.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Nov 2, 2026.
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