Mixtral 8x7B vs GPT-4o vs Claude Haiku 3
Claude Haiku 3 comes out ahead, 47 to 43 and 37 on our weighted score, and it is the cheaper option too.
Mistral AIMixtral 8x7B
37/100- ECI118.5
- Price$0.70 / $0.70
- Context32K
OpenAIGPT-4o
43/100- ECI129.0
- Price$2.50 / $10.00
- Context128K
- Our pick
AnthropicClaude Haiku 3
47/100- ECI118.4
- Price$0.25 / $1.25
- Context200K
Claude Haiku 3 is our pick
Claude Haiku 3 is the better all-round choice, scoring 47/100 against GPT-4o (43) and Mixtral 8x7B (37). It leads on price and context window. GPT-4o wins on capability and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGPT-4oCapabilities Index (ECI): GPT-4o 129.0 · Mixtral 8x7B 118.5 · Claude Haiku 3 118.4
- Lowest priceClaude Haiku 3Claude Haiku 3 $0.50 · Mixtral 8x7B $0.70 · GPT-4o $4.38 per 1M tokens (3:1 blend)
- Longest contextClaude Haiku 3Claude Haiku 3 200,000 · GPT-4o 128,000 · Mixtral 8x7B 32,000 tokens
- Widest inputsGPT-4o and Claude Haiku 3Mixtral 8x7B: Text · GPT-4o: Text, Images, PDFs · Claude Haiku 3: Text, Images, PDFs
- Self-hostingMixtral 8x7BPublishes downloadable weights
| Measure | Weight | Mixtral 8x7B | GPT-4o | Claude Haiku 3 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 38 | 52 | 38 |
| Price | 25% | 57 | 19 | 64 |
| Inputs & features | 15% | 25 | 70 | 60 |
| Context window | 10% | 0 | 24 | 32 |
| Overall | 100% | 37/100 | 43/100 | 47/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Mixtral 8x7BMistral AI | GPT-4oOpenAI | Claude Haiku 3Anthropic |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 118.5 | 129.0 (best) | 118.4 |
| ECI rank | #142 of 148 | #129 of 148 (best) | #143 of 148 |
| GPQA DiamondGraduate-level science questions | 30.6% | 48.9% (best) | 36.3% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 6.3% (best) | 1.8% |
| Price per million tokens | |||
| Input | $0.70 | $2.50 | $0.25 (best) |
| Output | $0.70 (best) | $10.00 | $1.25 |
| Cached input | — | $1.25 | — |
| Blended (3:1) | $0.70 | $4.38 | $0.50 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Mistral API | Official OpenAI API | Median of 2 providers |
| Limits | |||
| Context window | 32,000 tokens | 128,000 tokens | 200,000 tokens (best) |
| Max output | 32,000 tokens (best) | 16,384 tokens | 4,096 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | Yes | Yes |
| 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 | Proprietary | Proprietary |
| API model ID | open-mixtral-8x7b | gpt-4o | — |
| API providers | 1 | 19 (best) | 2 |
| Released | Dec 11, 2023 | May 13, 2024 | Mar 13, 2024 |
| Knowledge cutoff | Jan 2024 | Sep 2023 | Aug 31, 2023 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Mixtral 8x7B$8.40
- GPT-4o$45.00
- Claude Haiku 3$5.00
Which should you choose?
Which is better: Mixtral 8x7B, GPT-4o or Claude Haiku 3?
Claude Haiku 3 is the better all-round choice, scoring 47/100 against GPT-4o (43) and Mixtral 8x7B (37). It leads on price and context window. GPT-4o wins on capability and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Mixtral 8x7B, GPT-4o or Claude Haiku 3?
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); GPT-4o costs $2.50 input / $10.00 output per million tokens (official OpenAI 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 $4.38 for GPT-4o (8.8× as much).
Which scores higher on benchmarks?
GPT-4o scores higher on the Capabilities Index (ECI): GPT-4o 129.0 (#129 of 148), Mixtral 8x7B 118.5 (#142 of 148) and Claude Haiku 3 118.4 (#143 of 148). Their confidence ranges do not overlap (124.2–131.5 vs 111.3–121.3), so the gap is a real one. On individual benchmarks: GPQA Diamond — GPT-4o 48.9%, Claude Haiku 3 36.3%, Mixtral 8x7B 30.6%.
Which is better for coding?
There are no published SWE-bench Verified results for Mixtral 8x7B, GPT-4o and Claude Haiku 3 yet, so there is no like-for-like coding score. On overall capability, GPT-4o 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 128,000 for GPT-4o and 32,000 for Mixtral 8x7B. Maximum output per response: Mixtral 8x7B up to 32,000, GPT-4o up to 16,384, Claude Haiku 3 up to 4,096 tokens.
Which can read images, PDFs, audio or video?
Mixtral 8x7B accepts text; GPT-4o accepts text, images and PDFs; Claude Haiku 3 accepts text, images and PDFs. GPT-4o handles the widest range of inputs.
Are any of these open source?
Mixtral 8x7B publishes its weights and can be self-hosted; GPT-4o and Claude Haiku 3 is proprietary.
Which is newer?
GPT-4o is the newest, released May 13, 2024. Claude Haiku 3 came out Mar 13, 2024; Mixtral 8x7B came out Dec 11, 2023. Knowledge cutoff: Mixtral 8x7B Jan 2024, GPT-4o Sep 2023, Claude Haiku 3 Aug 31, 2023.
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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