Qwen3 235B-A22B Instruct 2507 vs Kimi K2 Instruct
Qwen3 235B-A22B Instruct 2507 comes out ahead, 57 to 50 on our weighted score, and it is the cheaper option too.
- Our pick
Alibaba (Qwen)Qwen3 235B-A22B Instruct 2507
57/100- ECI138.8
- Price$0.199 / $0.60
- Context262K
Moonshot AIKimi K2 Instruct
50/100- ECI139.9
- Price$0.57 / $2.30
- Context131K
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Qwen3 235B-A22B Instruct 2507 is our pick
Qwen3 235B-A22B Instruct 2507 is the better all-round choice, scoring 57/100 against Kimi K2 Instruct (50). It leads on price and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityKimi K2 InstructCapabilities Index (ECI): Kimi K2 Instruct 139.9 · Qwen3 235B-A22B Instruct 2507 138.8
- Lowest priceQwen3 235B-A22B Instruct 2507Qwen3 235B-A22B Instruct 2507 $0.299 · Kimi K2 Instruct $1.00 per 1M tokens (3:1 blend)
- Longest contextQwen3 235B-A22B Instruct 2507Qwen3 235B-A22B Instruct 2507 262,144 · Kimi K2 Instruct 131,072 tokens
- Widest inputsSame inputsQwen3 235B-A22B Instruct 2507: Text · Kimi K2 Instruct: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Qwen3 235B-A22B Instruct 2507 | Kimi K2 Instruct |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 63 | 64 |
| Price | 25% | 72 | 48 |
| Inputs & features | 15% | 25 | 25 |
| Context window | 10% | 37 | 25 |
| Overall | 100% | 57/100 | 50/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Qwen3 235B-A22B Instruct 2507Alibaba (Qwen) | Kimi K2 InstructMoonshot AI |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 138.8 | 139.9 (best) |
| ECI rank | #118 of 165 | #112 of 165 (best) |
| Price per million tokens | ||
| Input | $0.199 (best) | $0.57 |
| Output | $0.60 (best) | $2.30 |
| Cached input | — | — |
| Blended (3:1) | $0.299 (best) | $1.00 |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 23 providers | Median of 11 providers |
| Limits | ||
| Context window | 262,144 tokens (best) | 131,072 tokens |
| Max output | 16,384 tokens | 32,768 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | OpenApache 2.0 | OpenModified MIT |
| API model ID | — | — |
| API providers | 25 (best) | 11 |
| Released | Jul 21, 2025 | Jul 11, 2025 |
| Knowledge cutoff | — | — |
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 Instruct 2507$3.19
- Kimi K2 Instruct$10.30
Which should you choose?
Which is better: Qwen3 235B-A22B Instruct 2507 or Kimi K2 Instruct?
Qwen3 235B-A22B Instruct 2507 is the better all-round choice, scoring 57/100 against Kimi K2 Instruct (50). It leads on price and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Qwen3 235B-A22B Instruct 2507 or Kimi K2 Instruct?
Qwen3 235B-A22B Instruct 2507 is cheaper at $0.199 input / $0.60 output per million tokens (median across 23 API providers). Kimi K2 Instruct costs $0.57 input / $2.30 output per million tokens (median across 11 API providers). At a typical mix of three input tokens to one output token, that is $0.299 per million tokens for Qwen3 235B-A22B Instruct 2507 versus $1.00 for Kimi K2 Instruct (3.3× as much).
Which scores higher on benchmarks?
Kimi K2 Instruct scores higher on the Capabilities Index (ECI): Kimi K2 Instruct 139.9 (#112 of 165) and Qwen3 235B-A22B Instruct 2507 138.8 (#118 of 165). The confidence ranges of the top two overlap (136.3–141.6 vs 135.5–140.9), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3 235B-A22B Instruct 2507 and Kimi K2 Instruct yet, so there is no like-for-like coding score. On overall capability, Kimi K2 Instruct 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 Instruct 2507 has the largest context window at 262,144 tokens, against 131,072 for Kimi K2 Instruct. Maximum output per response: Qwen3 235B-A22B Instruct 2507 up to 16,384, Kimi K2 Instruct up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Qwen3 235B-A22B Instruct 2507 accepts text; Kimi K2 Instruct accepts text. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights (Apache 2.0 and Modified MIT), so you can self-host them.
Which is newer?
Qwen3 235B-A22B Instruct 2507 is the newest, released Jul 21, 2025. Kimi K2 Instruct came out Jul 11, 2025.
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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