DeepSeek V3 0324 vs Mistral Small 3.2 vs Qwen3 8B
Mistral Small 3.2 comes out ahead, 60 to 56 and 54 on our weighted score, and it is the cheaper option too.
DeepSeekDeepSeek V3 0324
54/100- ECI135.9
- Price$0.24 / $0.90
- Context164K
- Our pick
Mistral AIMistral Small 3.2
60/100- ECI131.7
- Price$0.10 / $0.30
- Context128K
Alibaba (Qwen)Qwen3 8B
56/100- ECI136.2
- Price$0.18 / $0.70
- Context131K
Mistral Small 3.2 is our pick
Mistral Small 3.2 is the better all-round choice, scoring 60/100 against Qwen3 8B (56) and DeepSeek V3 0324 (54). It leads on price and inputs & features. DeepSeek V3 0324 wins on context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityQwen3 8BCapabilities Index (ECI): Qwen3 8B 136.2 · DeepSeek V3 0324 135.9 · Mistral Small 3.2 131.7
- Lowest priceMistral Small 3.2Mistral Small 3.2 $0.15 · Qwen3 8B $0.31 · DeepSeek V3 0324 $0.405 per 1M tokens (3:1 blend)
- Longest contextDeepSeek V3 0324DeepSeek V3 0324 163,840 · Qwen3 8B 131,072 · Mistral Small 3.2 128,000 tokens
- Widest inputsMistral Small 3.2DeepSeek V3 0324: Text · Mistral Small 3.2: Text, Images · Qwen3 8B: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | DeepSeek V3 0324 | Mistral Small 3.2 | Qwen3 8B |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 60 | 55 | 61 |
| Price | 25% | 68 | 89 | 74 |
| Inputs & features | 15% | 25 | 50 | 35 |
| Context window | 10% | 28 | 24 | 24 |
| Overall | 100% | 54/100 | 60/100 | 56/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | DeepSeek V3 0324DeepSeek | Mistral Small 3.2Mistral AI | Qwen3 8BAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 135.9 | 131.7 | 136.2 (best) |
| ECI rank | #114 of 148 | #123 of 148 | #113 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 67.6% (best) | 49.1% | 56.8% |
| OTIS Mock AIME 2024–2025Competition mathematics | 37.8% | 30.3% | 56.1% (best) |
| Price per million tokens | |||
| Input | $0.24 | $0.10 (best) | $0.18 |
| Output | $0.90 | $0.30 (best) | $0.70 |
| Cached input | — | — | — |
| Blended (3:1) | $0.405 | $0.15 (best) | $0.31 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 5 providers | Official Mistral API | Official Alibaba API |
| Limits | |||
| Context window | 163,840 tokens (best) | 128,000 tokens | 131,072 tokens |
| Max output | 163,840 tokens (best) | 16,384 tokens | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Open | Open |
| API model ID | — | mistral-small-2506 | qwen3-8b |
| API providers | 5 | 6 (best) | 1 |
| Released | Mar 24, 2025 | Jun 20, 2025 | Apr 28, 2025 |
| Knowledge cutoff | — | Mar 2025 | Apr 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- DeepSeek V3 0324$4.20
- Mistral Small 3.2$1.60
- Qwen3 8B$3.20
Which should you choose?
Which is better: DeepSeek V3 0324, Mistral Small 3.2 or Qwen3 8B?
Mistral Small 3.2 is the better all-round choice, scoring 60/100 against Qwen3 8B (56) and DeepSeek V3 0324 (54). It leads on price and inputs & features. DeepSeek V3 0324 wins on context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, DeepSeek V3 0324, Mistral Small 3.2 or Qwen3 8B?
Mistral Small 3.2 is cheaper at $0.10 input / $0.30 output per million tokens (official Mistral API price). Qwen3 8B costs $0.18 input / $0.70 output per million tokens (official Alibaba API price); DeepSeek V3 0324 costs $0.24 input / $0.90 output per million tokens (median across 5 API providers). At a typical mix of three input tokens to one output token, that is $0.15 per million tokens for Mistral Small 3.2 versus $0.31 for Qwen3 8B (2.1× as much) and $0.405 for DeepSeek V3 0324 (2.7× as much).
Which scores higher on benchmarks?
Qwen3 8B scores higher on the Capabilities Index (ECI): Qwen3 8B 136.2 (#113 of 148), DeepSeek V3 0324 135.9 (#114 of 148) and Mistral Small 3.2 131.7 (#123 of 148). The confidence ranges of the top two overlap (129.7–138.1 vs 132.4–138.0), so treat the gap as small. On individual benchmarks: GPQA Diamond — DeepSeek V3 0324 67.6%, Qwen3 8B 56.8%, Mistral Small 3.2 49.1%; OTIS Mock AIME 2024–2025 — Qwen3 8B 56.1%, DeepSeek V3 0324 37.8%, Mistral Small 3.2 30.3%.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek V3 0324, Mistral Small 3.2 and Qwen3 8B 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. All three support tool calling for agent workflows.
Which has the bigger context window?
DeepSeek V3 0324 has the largest context window at 163,840 tokens, against 131,072 for Qwen3 8B and 128,000 for Mistral Small 3.2. Maximum output per response: DeepSeek V3 0324 up to 163,840, Mistral Small 3.2 up to 16,384, Qwen3 8B up to 8,192 tokens.
Which can read images, PDFs, audio or video?
DeepSeek V3 0324 accepts text; Mistral Small 3.2 accepts text and images; Qwen3 8B accepts text. Mistral Small 3.2 handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights, so you can self-host them.
Which is newer?
Mistral Small 3.2 is the newest, released Jun 20, 2025. Qwen3 8B came out Apr 28, 2025; DeepSeek V3 0324 came out Mar 24, 2025. Knowledge cutoff: Mistral Small 3.2 Mar 2025, Qwen3 8B Apr 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 Oct 4, 2026.
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