Mixtral 8x22B vs Mistral Small 3.1 24B vs GPT-4o
Mistral Small 3.1 24B comes out ahead, 55 to 43 and 33 on our weighted score, and it is the cheaper option too.
Mistral AI
Mixtral 8x22B
33/100- ECI122.0
- Price$2.00 / $6.00
- Context64K
- Our pick
Mistral AI
Mistral Small 3.1 24B
55/100- ECI127.5
- Price$0.229 / $0.436
- Context128K
OpenAI
GPT-4o
43/100- ECI129.0
- Price$2.50 / $10.00
- Context128K
Mistral Small 3.1 24B is our pick
Mistral Small 3.1 24B is the better all-round choice, scoring 55/100 against GPT-4o (43) and Mixtral 8x22B (33). It leads on price. 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 · Mistral Small 3.1 24B 127.5 · Mixtral 8x22B 122.0
- Lowest priceMistral Small 3.1 24BMistral Small 3.1 24B $0.281 · Mixtral 8x22B $3.00 · GPT-4o $4.38 per 1M tokens (3:1 blend)
- Longest contextMistral Small 3.1 24B and GPT-4oMistral Small 3.1 24B 128,000 · GPT-4o 128,000 · Mixtral 8x22B 64,000 tokens
- Widest inputsGPT-4oMixtral 8x22B: Text · Mistral Small 3.1 24B: Text, Images · GPT-4o: Text, Images, PDFs
- Self-hostingMixtral 8x22B and Mistral Small 3.1 24BPublishes downloadable weights
| Measure | Weight | Mixtral 8x22B | Mistral Small 3.1 24B | GPT-4o |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 43 | 50 | 52 |
| Price | 25% | 27 | 76 | 19 |
| Inputs & features | 15% | 25 | 60 | 70 |
| Context window | 10% | 12 | 24 | 24 |
| Overall | 100% | 33/100 | 55/100 | 43/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 122.0 | 127.5 | 129.0 (best) |
| ECI rank | #139 of 148 | #132 of 148 | #129 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 34.1% | 47.5% | 48.9% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 5.8% | 6.3% (best) |
| Price per million tokens | |||
| Input | $2.00 | $0.229 (best) | $2.50 |
| Output | $6.00 | $0.436 (best) | $10.00 |
| Cached input | — | — | $1.25 |
| Blended (3:1) | $3.00 | $0.281 (best) | $4.38 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Mistral API | Median of 2 providers | Official OpenAI API |
| Limits | |||
| Context window | 64,000 tokens | 128,000 tokens (best) | 128,000 tokens (best) |
| Max output | 64,000 tokens (best) | 16,384 tokens | 16,384 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | No | Yes |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | Yes |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | open-mixtral-8x22b | — | gpt-4o |
| API providers | 1 | 2 | 19 (best) |
| Released | Apr 17, 2024 | Mar 17, 2025 | May 13, 2024 |
| Knowledge cutoff | Apr 2024 | Jun 2024 | Sep 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 8x22B$32.00
Mistral Small 3.1 24B$3.16
GPT-4o$45.00
Which should you choose?
Which is better: Mixtral 8x22B, Mistral Small 3.1 24B or GPT-4o?
Mistral Small 3.1 24B is the better all-round choice, scoring 55/100 against GPT-4o (43) and Mixtral 8x22B (33). It leads on price. 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 8x22B, Mistral Small 3.1 24B or GPT-4o?
Mistral Small 3.1 24B is cheaper at $0.229 input / $0.436 output per million tokens (median across 2 API providers). Mixtral 8x22B costs $2.00 input / $6.00 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 $0.281 per million tokens for Mistral Small 3.1 24B versus $3.00 for Mixtral 8x22B (11× as much) and $4.38 for GPT-4o (16× as much).
Which scores higher on benchmarks?
GPT-4o scores higher on the Capabilities Index (ECI): GPT-4o 129.0 (#129 of 148), Mistral Small 3.1 24B 127.5 (#132 of 148) and Mixtral 8x22B 122.0 (#139 of 148). The confidence ranges of the top two overlap (124.2–131.5 vs 122.6–129.4), so treat the gap as small. On individual benchmarks: GPQA Diamond — GPT-4o 48.9%, Mistral Small 3.1 24B 47.5%, Mixtral 8x22B 34.1%.
Which is better for coding?
There are no published SWE-bench Verified results for Mixtral 8x22B, Mistral Small 3.1 24B and GPT-4o 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?
Mistral Small 3.1 24B and GPT-4o have the largest context windows (128,000 and 128,000 tokens), against 64,000 for Mixtral 8x22B. Maximum output per response: Mixtral 8x22B up to 64,000, Mistral Small 3.1 24B up to 16,384, GPT-4o up to 16,384 tokens.
Which can read images, PDFs, audio or video?
Mixtral 8x22B accepts text; Mistral Small 3.1 24B accepts text and images; GPT-4o accepts text, images and PDFs. GPT-4o handles the widest range of inputs.
Are any of these open source?
Mixtral 8x22B and Mistral Small 3.1 24B publishes its weights and can be self-hosted; GPT-4o is proprietary.
Which is newer?
Mistral Small 3.1 24B is the newest, released Mar 17, 2025. GPT-4o came out May 13, 2024; Mixtral 8x22B came out Apr 17, 2024. Knowledge cutoff: Mixtral 8x22B Apr 2024, Mistral Small 3.1 24B Jun 2024, GPT-4o Sep 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.