Ministral 8B Instruct vs Mistral Large 2.1 vs Qwen2.5 72B Instruct
Ministral 8B Instruct comes out ahead, 42 to 39 and 39 on our weighted score, and it is the cheaper option too.
- Our pick
Mistral AI
Ministral 8B Instruct
42/100- ECI—
- Price$0.15 / $0.15
- Context131K
Mistral AI
Mistral Large 2.1
39/100- ECI128.5
- Price$2.00 / $6.00
- Context131K
Alibaba (Qwen)
Qwen2.5 72B Instruct
39/100- ECI129.0
- Price$1.40 / $5.60
- Context131K
Ministral 8B Instruct is our pick
Ministral 8B Instruct is the better all-round choice, scoring 42/100 against Mistral Large 2.1 (39) and Qwen2.5 72B Instruct (39). It leads on price. Mistral Large 2.1 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond), because Ministral 8B Instruct has no Capabilities Index score yet.
- CapabilityMistral Large 2.1Shared benchmarks: Mistral Large 2.1 51.3% · Qwen2.5 72B Instruct 49.2% · Ministral 8B Instruct 27.2%
- Lowest priceMinistral 8B InstructMinistral 8B Instruct $0.15 · Qwen2.5 72B Instruct $2.45 · Mistral Large 2.1 $3.00 per 1M tokens (3:1 blend)
- Longest contextAbout the sameMinistral 8B Instruct 131,072 · Mistral Large 2.1 131,072 · Qwen2.5 72B Instruct 131,072 tokens
- Widest inputsSame inputsMinistral 8B Instruct: Text · Mistral Large 2.1: Text · Qwen2.5 72B Instruct: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Ministral 8B Instruct | Mistral Large 2.1 | Qwen2.5 72B Instruct |
|---|---|---|---|---|
| CapabilityShared benchmarks | 50% | 27 | 51 | 49 |
| Price | 25% | 89 | 27 | 31 |
| Inputs & features | 15% | 25 | 25 | 25 |
| Context window | 10% | 24 | 24 | 24 |
| Overall | 100% | 42/100 | 39/100 | 39/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | 128.5 | 129.0 (best) |
| ECI rank | — | #130 of 148 | #128 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 27.2% | 51.3% (best) | 49.2% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 7.8% | 8.1% (best) |
| Price per million tokens | |||
| Input | $0.15 (best) | $2.00 | $1.40 |
| Output | $0.15 (best) | $6.00 | $5.60 |
| Cached input | — | — | — |
| Blended (3:1) | $0.15 (best) | $3.00 | $2.45 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 1 providers | Official Mistral API | Official Alibaba API |
| Limits | |||
| Context window | 131,072 tokens | 131,072 tokens | 131,072 tokens |
| Max output | 8,192 tokens | 16,384 tokens (best) | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | 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 | No | No |
| Availability | |||
| Weights | OpenMistral Research License | Open | Open |
| API model ID | — | mistral-large-2411 | qwen2-5-72b-instruct |
| API providers | 1 | 2 (best) | 1 |
| Released | Oct 16, 2024 | Nov 18, 2024 | Sep 19, 2024 |
| Knowledge cutoff | — | Nov 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.
Ministral 8B Instruct$1.80
Mistral Large 2.1$32.00
Qwen2.5 72B Instruct$25.20
Which should you choose?
Which is better: Ministral 8B Instruct, Mistral Large 2.1 or Qwen2.5 72B Instruct?
Ministral 8B Instruct is the better all-round choice, scoring 42/100 against Mistral Large 2.1 (39) and Qwen2.5 72B Instruct (39). It leads on price. Mistral Large 2.1 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond), because Ministral 8B Instruct has no Capabilities Index score yet.
Which is cheaper, Ministral 8B Instruct, Mistral Large 2.1 or Qwen2.5 72B Instruct?
Ministral 8B Instruct is cheaper at $0.15 input / $0.15 output per million tokens (median across 1 API provider). 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 $0.15 per million tokens for Ministral 8B Instruct versus $2.45 for Qwen2.5 72B Instruct (16× as much) and $3.00 for Mistral Large 2.1 (20× as much).
Which scores higher on benchmarks?
Not every model here has a Capabilities Index score, so we compare the average of shared benchmarks (GPQA Diamond): Mistral Large 2.1 51.3%, Qwen2.5 72B Instruct 49.2% and Ministral 8B Instruct 27.2%. On individual benchmarks: GPQA Diamond — Mistral Large 2.1 51.3%, Qwen2.5 72B Instruct 49.2%, Ministral 8B Instruct 27.2%.
Which is better for coding?
There are no published SWE-bench Verified results for Ministral 8B Instruct, Mistral Large 2.1 and Qwen2.5 72B Instruct yet, so there is no like-for-like coding score. On overall capability, Mistral Large 2.1 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?
Ministral 8B Instruct, Mistral Large 2.1 and Qwen2.5 72B Instruct share the same 131,072-token context window. Maximum output per response: Ministral 8B Instruct up to 8,192, Mistral Large 2.1 up to 16,384, Qwen2.5 72B Instruct up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Ministral 8B Instruct accepts text; Mistral Large 2.1 accepts text; Qwen2.5 72B Instruct accepts text. They handle the same number of input types.
Are any of these open source?
Yes, all three publish their weights (Mistral Research License), so you can self-host them.
Which is newer?
Mistral Large 2.1 is the newest, released Nov 18, 2024. Ministral 8B Instruct came out Oct 16, 2024; Qwen2.5 72B Instruct came out Sep 19, 2024. Knowledge cutoff: Mistral Large 2.1 Nov 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.