Mistral Large 2.1 vs Claude Haiku 3 vs Qwen2.5 72B Instruct
Claude Haiku 3 comes out ahead, 47 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 pick
AnthropicClaude Haiku 3
47/100- ECI118.4
- Price$0.25 / $1.25
- Context200K
Alibaba (Qwen)Qwen2.5 72B Instruct
40/100- ECI129.0
- Price$1.40 / $5.60
- Context131K
Claude Haiku 3 is our pick
Claude Haiku 3 is the better all-round choice, scoring 47/100 against Qwen2.5 72B Instruct (40) and Mistral Large 2.1 (38). It leads on price, inputs & features and context window. 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 · Claude Haiku 3 118.4
- Lowest priceClaude Haiku 3Claude Haiku 3 $0.50 · Qwen2.5 72B Instruct $2.45 · Mistral Large 2.1 $3.00 per 1M tokens (3:1 blend)
- Longest contextClaude Haiku 3Claude Haiku 3 200,000 · Mistral Large 2.1 131,072 · Qwen2.5 72B Instruct 131,072 tokens
- Widest inputsClaude Haiku 3Mistral Large 2.1: Text · Claude Haiku 3: Text, Images, PDFs · Qwen2.5 72B Instruct: Text
- Self-hostingMistral Large 2.1 and Qwen2.5 72B InstructPublishes downloadable weights
| Measure | Weight | Mistral Large 2.1 | Claude Haiku 3 | Qwen2.5 72B Instruct |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 51 | 38 | 52 |
| Price | 25% | 27 | 64 | 31 |
| Inputs & features | 15% | 25 | 60 | 25 |
| Context window | 10% | 24 | 32 | 24 |
| Overall | 100% | 38/100 | 47/100 | 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 | Claude Haiku 3Anthropic | Qwen2.5 72B InstructAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 128.5 | 118.4 | 129.0 (best) |
| ECI rank | #130 of 148 | #143 of 148 | #128 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 51.3% (best) | 36.3% | 49.2% |
| OTIS Mock AIME 2024–2025Competition mathematics | 7.8% | 1.8% | 8.1% (best) |
| Price per million tokens | |||
| Input | $2.00 | $0.25 (best) | $1.40 |
| Output | $6.00 | $1.25 (best) | $5.60 |
| Cached input | — | — | — |
| Blended (3:1) | $3.00 | $0.50 (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 | 200,000 tokens (best) | 131,072 tokens |
| Max output | 16,384 tokens (best) | 4,096 tokens | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | Yes | 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 | Open | Proprietary | Open |
| API model ID | mistral-large-2411 | — | qwen2-5-72b-instruct |
| API providers | 2 (best) | 2 (best) | 1 |
| Released | Nov 18, 2024 | Mar 13, 2024 | Sep 19, 2024 |
| Knowledge cutoff | Nov 2024 | Aug 31, 2023 | 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
- Claude Haiku 3$5.00
- Qwen2.5 72B Instruct$25.20
Which should you choose?
Which is better: Mistral Large 2.1, Claude Haiku 3 or Qwen2.5 72B Instruct?
Claude Haiku 3 is the better all-round choice, scoring 47/100 against Qwen2.5 72B Instruct (40) and Mistral Large 2.1 (38). It leads on price, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Mistral Large 2.1, Claude Haiku 3 or Qwen2.5 72B Instruct?
Claude Haiku 3 is cheaper at $0.25 input / $1.25 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 $0.50 per million tokens for Claude Haiku 3 versus $2.45 for Qwen2.5 72B Instruct (4.9× as much) and $3.00 for Mistral Large 2.1 (6× 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 Claude Haiku 3 118.4 (#143 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%, Claude Haiku 3 36.3%; OTIS Mock AIME 2024–2025 — Qwen2.5 72B Instruct 8.1%, Mistral Large 2.1 7.8%, Claude Haiku 3 1.8%.
Which is better for coding?
There are no published SWE-bench Verified results for Mistral Large 2.1, Claude Haiku 3 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?
Claude Haiku 3 has the largest context window at 200,000 tokens, against 131,072 for Mistral Large 2.1 and 131,072 for Qwen2.5 72B Instruct. Maximum output per response: Mistral Large 2.1 up to 16,384, Claude Haiku 3 up to 4,096, Qwen2.5 72B Instruct up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Mistral Large 2.1 accepts text; Claude Haiku 3 accepts text, images and PDFs; Qwen2.5 72B Instruct accepts text. Claude Haiku 3 handles the widest range of inputs.
Are any of these open source?
Mistral Large 2.1 and Qwen2.5 72B Instruct publishes its weights and can be self-hosted; Claude Haiku 3 is proprietary.
Which is newer?
Mistral Large 2.1 is the newest, released Nov 18, 2024. Qwen2.5 72B Instruct came out Sep 19, 2024; Claude Haiku 3 came out Mar 13, 2024. Knowledge cutoff: Mistral Large 2.1 Nov 2024, Claude Haiku 3 Aug 31, 2023, 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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