Claude Haiku 3.5 vs Qwen2.5 7B Instruct vs Mistral Large 2.1
Qwen2.5 7B Instruct comes out ahead, 50 to 46 and 38 on our weighted score, and it is the cheaper option too.
AnthropicClaude Haiku 3.5
46/100- ECI127.0
- Price$0.80 / $4.00
- Context200K
- Our pick
Alibaba (Qwen)Qwen2.5 7B Instruct
50/100- ECI118.5
- Price$0.05 / $0.10
- Context131K
Mistral AIMistral Large 2.1
38/100- ECI128.6
- Price$2.00 / $6.00
- Context131K
Qwen2.5 7B Instruct is our pick
Qwen2.5 7B Instruct is the better all-round choice, scoring 50/100 against Claude Haiku 3.5 (46) and Mistral Large 2.1 (38). It leads on price. Claude Haiku 3.5 wins on inputs & features and context window. Mistral Large 2.1 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityMistral Large 2.1Capabilities Index (ECI): Mistral Large 2.1 128.6 · Claude Haiku 3.5 127.0 · Qwen2.5 7B Instruct 118.5
- Lowest priceQwen2.5 7B InstructQwen2.5 7B Instruct $0.063 · Claude Haiku 3.5 $1.60 · Mistral Large 2.1 $3.00 per 1M tokens (3:1 blend)
- Longest contextClaude Haiku 3.5Claude Haiku 3.5 200,000 · Qwen2.5 7B Instruct 131,072 · Mistral Large 2.1 131,072 tokens
- Widest inputsClaude Haiku 3.5Claude Haiku 3.5: Text, Images, PDFs · Qwen2.5 7B Instruct: Text · Mistral Large 2.1: Text
- Self-hostingQwen2.5 7B Instruct and Mistral Large 2.1Publishes downloadable weights (Apache 2.0)
| Measure | Weight | Claude Haiku 3.5 | Qwen2.5 7B Instruct | Mistral Large 2.1 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 48 | 38 | 50 |
| Price | 25% | 38 | 100 | 26 |
| Inputs & features | 15% | 60 | 25 | 25 |
| Context window | 10% | 32 | 25 | 25 |
| Overall | 100% | 46/100 | 50/100 | 38/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Claude Haiku 3.5Anthropic | Qwen2.5 7B InstructAlibaba (Qwen) | Mistral Large 2.1Mistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 127.0 | 118.5 | 128.6 (best) |
| ECI rank | #147 of 165 | #159 of 165 | #142 of 165 (best) |
| GPQA DiamondGraduate-level science questions | 38.1% | 35.5% | 51.3% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 4.3% | 2.5% | 7.8% (best) |
| Price per million tokens | |||
| Input | $0.80 | $0.05 (best) | $2.00 |
| Output | $4.00 | $0.10 (best) | $6.00 |
| Cached input | — | — | — |
| Blended (3:1) | $1.60 | $0.063 (best) | $3.00 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 3 providers | Median of 3 providers | Median of 2 providers |
| Limits | |||
| Context window | 200,000 tokens (best) | 131,072 tokens | 131,072 tokens |
| Max output | 8,192 tokens | 8,192 tokens | 16,384 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | Yes | 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 | Proprietary | OpenApache 2.0 | Open |
| API model ID | — | — | — |
| API providers | 4 (best) | 4 (best) | 2 |
| Released | Oct 22, 2024 | Sep 19, 2024 | Nov 18, 2024 |
| Knowledge cutoff | Jul 31, 2024 | — | Nov 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Claude Haiku 3.5$16.00
- Qwen2.5 7B Instruct$0.70
- Mistral Large 2.1$32.00
Which should you choose?
Which is better: Claude Haiku 3.5, Qwen2.5 7B Instruct or Mistral Large 2.1?
Qwen2.5 7B Instruct is the better all-round choice, scoring 50/100 against Claude Haiku 3.5 (46) and Mistral Large 2.1 (38). It leads on price. Claude Haiku 3.5 wins on inputs & features and context window. Mistral Large 2.1 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Claude Haiku 3.5, Qwen2.5 7B Instruct or Mistral Large 2.1?
Qwen2.5 7B Instruct is cheaper at $0.05 input / $0.10 output per million tokens (median across 3 API providers). Claude Haiku 3.5 costs $0.80 input / $4.00 output per million tokens (median across 3 API providers); Mistral Large 2.1 costs $2.00 input / $6.00 output per million tokens (median across 2 API providers). At a typical mix of three input tokens to one output token, that is $0.063 per million tokens for Qwen2.5 7B Instruct versus $1.60 for Claude Haiku 3.5 (26× as much) and $3.00 for Mistral Large 2.1 (48× as much).
Which scores higher on benchmarks?
Mistral Large 2.1 scores higher on the Capabilities Index (ECI): Mistral Large 2.1 128.6 (#142 of 165), Claude Haiku 3.5 127.0 (#147 of 165) and Qwen2.5 7B Instruct 118.5 (#159 of 165). The confidence ranges of the top two overlap (124.3–130.7 vs 121.4–129.2), so treat the gap as small. On individual benchmarks: GPQA Diamond — Mistral Large 2.1 51.3%, Claude Haiku 3.5 38.1%, Qwen2.5 7B Instruct 35.5%; OTIS Mock AIME 2024–2025 — Mistral Large 2.1 7.8%, Claude Haiku 3.5 4.3%, Qwen2.5 7B Instruct 2.5%.
Which is better for coding?
There are no published SWE-bench Verified results for Claude Haiku 3.5, Qwen2.5 7B Instruct and Mistral Large 2.1 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?
Claude Haiku 3.5 has the largest context window at 200,000 tokens, against 131,072 for Qwen2.5 7B Instruct and 131,072 for Mistral Large 2.1. Maximum output per response: Claude Haiku 3.5 up to 8,192, Qwen2.5 7B Instruct up to 8,192, Mistral Large 2.1 up to 16,384 tokens.
Which can read images, PDFs, audio or video?
Claude Haiku 3.5 accepts text, images and PDFs; Qwen2.5 7B Instruct accepts text; Mistral Large 2.1 accepts text. Claude Haiku 3.5 handles the widest range of inputs.
Are any of these open source?
Qwen2.5 7B Instruct and Mistral Large 2.1 publishes its weights (Apache 2.0) and can be self-hosted; Claude Haiku 3.5 is proprietary.
Which is newer?
Mistral Large 2.1 is the newest, released Nov 18, 2024. Claude Haiku 3.5 came out Oct 22, 2024; Qwen2.5 7B Instruct came out Sep 19, 2024. Knowledge cutoff: Claude Haiku 3.5 Jul 31, 2024, Mistral Large 2.1 Nov 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 Nov 2, 2026.
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