Claude Haiku 3 vs Mixtral 8x7B vs Qwen2.5 32B Instruct
Claude Haiku 3 comes out ahead, 47 to 43 and 37 on our weighted score, and it is the cheaper option too.
- Our pick
Anthropic
Claude Haiku 3
47/100- ECI118.4
- Price$0.25 / $1.25
- Context200K
Mistral AI
Mixtral 8x7B
37/100- ECI118.5
- Price$0.70 / $0.70
- Context32K
Alibaba (Qwen)
Qwen2.5 32B Instruct
43/100- ECI128.5
- Price$0.70 / $2.80
- Context131K
Claude Haiku 3 is our pick
Claude Haiku 3 is the better all-round choice, scoring 47/100 against Qwen2.5 32B Instruct (43) and Mixtral 8x7B (37). It leads on price, inputs & features and context window. Qwen2.5 32B Instruct wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityQwen2.5 32B InstructCapabilities Index (ECI): Qwen2.5 32B Instruct 128.5 · Mixtral 8x7B 118.5 · Claude Haiku 3 118.4
- Lowest priceClaude Haiku 3Claude Haiku 3 $0.50 · Mixtral 8x7B $0.70 · Qwen2.5 32B Instruct $1.23 per 1M tokens (3:1 blend)
- Longest contextClaude Haiku 3Claude Haiku 3 200,000 · Qwen2.5 32B Instruct 131,072 · Mixtral 8x7B 32,000 tokens
- Widest inputsClaude Haiku 3Claude Haiku 3: Text, Images, PDFs · Mixtral 8x7B: Text · Qwen2.5 32B Instruct: Text
- Self-hostingMixtral 8x7B and Qwen2.5 32B InstructPublishes downloadable weights
| Measure | Weight | Claude Haiku 3 | Mixtral 8x7B | Qwen2.5 32B Instruct |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 38 | 38 | 51 |
| Price | 25% | 64 | 57 | 46 |
| Inputs & features | 15% | 60 | 25 | 25 |
| Context window | 10% | 32 | 0 | 24 |
| Overall | 100% | 47/100 | 37/100 | 43/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 118.4 | 118.5 | 128.5 (best) |
| ECI rank | #143 of 148 | #142 of 148 | #131 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 36.3% | 30.6% | 46.1% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 1.8% | — | 7.4% (best) |
| Price per million tokens | |||
| Input | $0.25 (best) | $0.70 | $0.70 |
| Output | $1.25 | $0.70 (best) | $2.80 |
| Cached input | — | — | — |
| Blended (3:1) | $0.50 (best) | $0.70 | $1.23 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 2 providers | Official Mistral API | Official Alibaba API |
| Limits | |||
| Context window | 200,000 tokens (best) | 32,000 tokens | 131,072 tokens |
| Max output | 4,096 tokens | 32,000 tokens (best) | 8,192 tokens |
| 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 | Open | Open |
| API model ID | — | open-mixtral-8x7b | qwen2-5-32b-instruct |
| API providers | 2 (best) | 1 | 1 |
| Released | Mar 13, 2024 | Dec 11, 2023 | Sep 17, 2024 |
| Knowledge cutoff | Aug 31, 2023 | Jan 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.
Claude Haiku 3$5.00
Mixtral 8x7B$8.40
Qwen2.5 32B Instruct$12.60
Which should you choose?
Which is better: Claude Haiku 3, Mixtral 8x7B or Qwen2.5 32B Instruct?
Claude Haiku 3 is the better all-round choice, scoring 47/100 against Qwen2.5 32B Instruct (43) and Mixtral 8x7B (37). It leads on price, inputs & features and context window. Qwen2.5 32B Instruct wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Claude Haiku 3, Mixtral 8x7B or Qwen2.5 32B Instruct?
Claude Haiku 3 is cheaper at $0.25 input / $1.25 output per million tokens (median across 2 API providers). Mixtral 8x7B costs $0.70 input / $0.70 output per million tokens (official Mistral API price); Qwen2.5 32B Instruct costs $0.70 input / $2.80 output per million tokens (official Alibaba 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 $0.70 for Mixtral 8x7B (1.4× as much) and $1.23 for Qwen2.5 32B Instruct (2.5× as much).
Which scores higher on benchmarks?
Qwen2.5 32B Instruct scores higher on the Capabilities Index (ECI): Qwen2.5 32B Instruct 128.5 (#131 of 148), Mixtral 8x7B 118.5 (#142 of 148) and Claude Haiku 3 118.4 (#143 of 148). Their confidence ranges do not overlap (123.5–130.0 vs 111.3–121.3), so the gap is a real one. On individual benchmarks: GPQA Diamond — Qwen2.5 32B Instruct 46.1%, Claude Haiku 3 36.3%, Mixtral 8x7B 30.6%.
Which is better for coding?
There are no published SWE-bench Verified results for Claude Haiku 3, Mixtral 8x7B and Qwen2.5 32B Instruct yet, so there is no like-for-like coding score. On overall capability, Qwen2.5 32B 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 Qwen2.5 32B Instruct and 32,000 for Mixtral 8x7B. Maximum output per response: Claude Haiku 3 up to 4,096, Mixtral 8x7B up to 32,000, Qwen2.5 32B Instruct up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Claude Haiku 3 accepts text, images and PDFs; Mixtral 8x7B accepts text; Qwen2.5 32B Instruct accepts text. Claude Haiku 3 handles the widest range of inputs.
Are any of these open source?
Mixtral 8x7B and Qwen2.5 32B Instruct publishes its weights and can be self-hosted; Claude Haiku 3 is proprietary.
Which is newer?
Qwen2.5 32B Instruct is the newest, released Sep 17, 2024. Claude Haiku 3 came out Mar 13, 2024; Mixtral 8x7B came out Dec 11, 2023. Knowledge cutoff: Claude Haiku 3 Aug 31, 2023, Mixtral 8x7B Jan 2024, Qwen2.5 32B 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.