Mistral Large 2.1 vs Mistral Small 3.1 24B vs Qwen2.5 72B Instruct
Mistral Small 3.1 24B comes out ahead, 55 to 40 and 38 on our weighted score, and it is the cheaper option too.
Mistral AIMistral Large 2.1
38/100- ECI128.5
- Price$2.00 / $6.00
- Context131K
- Our pickMistral AI
Mistral Small 3.1 24B
55/100- ECI127.5
- Price$0.229 / $0.436
- Context128K
Alibaba (Qwen)Qwen2.5 72B Instruct
40/100- ECI129.0
- Price$1.40 / $5.60
- Context131K
Mistral Small 3.1 24B is our pick
Mistral Small 3.1 24B is the better all-round choice, scoring 55/100 against Qwen2.5 72B Instruct (40) and Mistral Large 2.1 (38). It leads on price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityQwen2.5 72B InstructCapabilities Index (ECI): Qwen2.5 72B Instruct 129.0 · Mistral Large 2.1 128.5 · Mistral Small 3.1 24B 127.5
- Lowest priceMistral Small 3.1 24BMistral Small 3.1 24B $0.281 · Qwen2.5 72B Instruct $2.45 · Mistral Large 2.1 $3.00 per 1M tokens (3:1 blend)
- Longest contextMistral Large 2.1 and Qwen2.5 72B InstructMistral Large 2.1 131,072 · Qwen2.5 72B Instruct 131,072 · Mistral Small 3.1 24B 128,000 tokens
- Widest inputsMistral Small 3.1 24BMistral Large 2.1: Text · Mistral Small 3.1 24B: Text, Images · Qwen2.5 72B Instruct: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Mistral Large 2.1 | Mistral Small 3.1 24B | Qwen2.5 72B Instruct |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 51 | 50 | 52 |
| Price | 25% | 27 | 76 | 31 |
| Inputs & features | 15% | 25 | 60 | 25 |
| Context window | 10% | 24 | 24 | 24 |
| Overall | 100% | 38/100 | 55/100 | 40/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Mistral Large 2.1Mistral AI | Mistral Small 3.1 24BMistral AI | Qwen2.5 72B InstructAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 128.5 | 127.5 | 129.0 (best) |
| ECI rank | #130 of 148 | #132 of 148 | #128 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 51.3% (best) | 47.5% | 49.2% |
| OTIS Mock AIME 2024–2025Competition mathematics | 7.8% | 5.8% | 8.1% (best) |
| Price per million tokens | |||
| Input | $2.00 | $0.229 (best) | $1.40 |
| Output | $6.00 | $0.436 (best) | $5.60 |
| Cached input | — | — | — |
| Blended (3:1) | $3.00 | $0.281 (best) | $2.45 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Mistral API | Median of 2 providers | Official Alibaba API |
| Limits | |||
| Context window | 131,072 tokens (best) | 128,000 tokens | 131,072 tokens (best) |
| Max output | 16,384 tokens (best) | 16,384 tokens (best) | 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 | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Open | Open | Open |
| API model ID | mistral-large-2411 | — | qwen2-5-72b-instruct |
| API providers | 2 (best) | 2 (best) | 1 |
| Released | Nov 18, 2024 | Mar 17, 2025 | Sep 19, 2024 |
| Knowledge cutoff | Nov 2024 | Jun 2024 | Apr 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Mistral Large 2.1$32.00
- Mistral Small 3.1 24B$3.16
- Qwen2.5 72B Instruct$25.20
Which should you choose?
Which is better: Mistral Large 2.1, Mistral Small 3.1 24B or Qwen2.5 72B Instruct?
Mistral Small 3.1 24B is the better all-round choice, scoring 55/100 against Qwen2.5 72B Instruct (40) and Mistral Large 2.1 (38). It leads on price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Mistral Large 2.1, Mistral Small 3.1 24B or Qwen2.5 72B Instruct?
Mistral Small 3.1 24B is cheaper at $0.229 input / $0.436 output per million tokens (median across 2 API providers). Qwen2.5 72B Instruct costs $1.40 input / $5.60 output per million tokens (official Alibaba API price); Mistral Large 2.1 costs $2.00 input / $6.00 output per million tokens (official Mistral 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 $2.45 for Qwen2.5 72B Instruct (8.7× as much) and $3.00 for Mistral Large 2.1 (11× as much).
Which scores higher on benchmarks?
Qwen2.5 72B Instruct scores higher on the Capabilities Index (ECI): Qwen2.5 72B Instruct 129.0 (#128 of 148), Mistral Large 2.1 128.5 (#130 of 148) and Mistral Small 3.1 24B 127.5 (#132 of 148). The confidence ranges of the top two overlap (123.8–130.7 vs 123.8–130.8), so treat the gap as small. On individual benchmarks: GPQA Diamond — Mistral Large 2.1 51.3%, Qwen2.5 72B Instruct 49.2%, Mistral Small 3.1 24B 47.5%; OTIS Mock AIME 2024–2025 — Qwen2.5 72B Instruct 8.1%, Mistral Large 2.1 7.8%, Mistral Small 3.1 24B 5.8%.
Which is better for coding?
There are no published SWE-bench Verified results for Mistral Large 2.1, Mistral Small 3.1 24B and Qwen2.5 72B Instruct yet, so there is no like-for-like coding score. On overall capability, Qwen2.5 72B Instruct 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?
Mistral Large 2.1 and Qwen2.5 72B Instruct have the largest context windows (131,072 and 131,072 tokens), against 128,000 for Mistral Small 3.1 24B. Maximum output per response: Mistral Large 2.1 up to 16,384, Mistral Small 3.1 24B up to 16,384, Qwen2.5 72B Instruct up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Mistral Large 2.1 accepts text; Mistral Small 3.1 24B accepts text and images; Qwen2.5 72B Instruct accepts text. Mistral Small 3.1 24B 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 3.1 24B is the newest, released Mar 17, 2025. Mistral Large 2.1 came out Nov 18, 2024; Qwen2.5 72B Instruct came out Sep 19, 2024. Knowledge cutoff: Mistral Large 2.1 Nov 2024, Mistral Small 3.1 24B Jun 2024, Qwen2.5 72B Instruct Apr 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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