Qwen3 8B vs Mistral Small 3.1 24B
Too close to call on our weighted score (Qwen3 8B 56, Mistral Small 3.1 24B 55). The right pick depends on what you value most.
Alibaba (Qwen)Qwen3 8B
56/100- ECI136.2
- Price$0.18 / $0.70
- Context131K
Mistral AIMistral Small 3.1 24B
55/100- ECI127.5
- Price$0.229 / $0.436
- Context128K
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Too close to call
It is close. Our weighted score puts them within 1 points (Qwen3 8B 56/100, Mistral Small 3.1 24B 55/100), so choose by what matters most for your work: Qwen3 8B for raw capability and Mistral Small 3.1 24B on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityQwen3 8BCapabilities Index (ECI): Qwen3 8B 136.2 · Mistral Small 3.1 24B 127.5
- Lowest priceMistral Small 3.1 24BMistral Small 3.1 24B $0.281 · Qwen3 8B $0.31 per 1M tokens (3:1 blend)
- Longest contextQwen3 8BQwen3 8B 131,072 · Mistral Small 3.1 24B 128,000 tokens
- Widest inputsMistral Small 3.1 24BQwen3 8B: Text · Mistral Small 3.1 24B: Text, Images
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Qwen3 8B | Mistral Small 3.1 24B |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 61 | 50 |
| Price | 25% | 74 | 76 |
| Inputs & features | 15% | 35 | 60 |
| Context window | 10% | 24 | 24 |
| Overall | 100% | 56/100 | 55/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Qwen3 8BAlibaba (Qwen) | Mistral Small 3.1 24BMistral AI |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 136.2 (best) | 127.5 |
| ECI rank | #113 of 148 (best) | #132 of 148 |
| GPQA DiamondGraduate-level science questions | 56.8% (best) | 47.5% |
| OTIS Mock AIME 2024–2025Competition mathematics | 56.1% (best) | 5.8% |
| Price per million tokens | ||
| Input | $0.18 (best) | $0.229 |
| Output | $0.70 | $0.436 (best) |
| Cached input | — | — |
| Blended (3:1) | $0.31 | $0.281 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official Alibaba API | Median of 2 providers |
| Limits | ||
| Context window | 131,072 tokens (best) | 128,000 tokens |
| Max output | 8,192 tokens | 16,384 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | Yes |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yes | No |
| Tool calling | Yes | Yes |
| Structured output | No | Yes |
| Availability | ||
| Weights | Open | Open |
| API model ID | qwen3-8b | — |
| API providers | 1 | 2 (best) |
| Released | Apr 28, 2025 | Mar 17, 2025 |
| Knowledge cutoff | Apr 2025 | Jun 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 8B$3.20
- Mistral Small 3.1 24B$3.16
Which should you choose?
Which is better: Qwen3 8B or Mistral Small 3.1 24B?
It is close. Our weighted score puts them within 1 points (Qwen3 8B 56/100, Mistral Small 3.1 24B 55/100), so choose by what matters most for your work: Qwen3 8B for raw capability and Mistral Small 3.1 24B on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Qwen3 8B or Mistral Small 3.1 24B?
Mistral Small 3.1 24B is cheaper at $0.229 input / $0.436 output per million tokens (median across 2 API providers). Qwen3 8B costs $0.18 input / $0.70 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.281 per million tokens for Mistral Small 3.1 24B versus $0.31 for Qwen3 8B (1.1× as much).
Which scores higher on benchmarks?
Qwen3 8B scores higher on the Capabilities Index (ECI): Qwen3 8B 136.2 (#113 of 148) and Mistral Small 3.1 24B 127.5 (#132 of 148). Their confidence ranges do not overlap (129.7–138.1 vs 122.6–129.4), so the gap is a real one. On individual benchmarks: GPQA Diamond — Qwen3 8B 56.8%, Mistral Small 3.1 24B 47.5%; OTIS Mock AIME 2024–2025 — Qwen3 8B 56.1%, Mistral Small 3.1 24B 5.8%.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3 8B and Mistral Small 3.1 24B yet, so there is no like-for-like coding score. On overall capability, Qwen3 8B 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 8B has the largest context window at 131,072 tokens, against 128,000 for Mistral Small 3.1 24B. Maximum output per response: Qwen3 8B up to 8,192, Mistral Small 3.1 24B up to 16,384 tokens.
Which can read images, PDFs, audio or video?
Qwen3 8B accepts text; Mistral Small 3.1 24B accepts text and images. Mistral Small 3.1 24B handles the widest range of inputs.
Are any of these open source?
Yes, both publish their weights, so you can self-host them.
Which is newer?
Qwen3 8B is the newest, released Apr 28, 2025. Mistral Small 3.1 24B came out Mar 17, 2025. Knowledge cutoff: Qwen3 8B Apr 2025, Mistral Small 3.1 24B Jun 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 Oct 4, 2026.
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