Mixtral 8x22B vs Mixtral 8x7B vs GPT-4o
GPT-4o comes out ahead, 43 to 37 and 33 on our weighted score, though Mixtral 8x7B is 6.3× cheaper per token.
Mistral AI
Mixtral 8x22B
33/100- ECI122.0
- Price$2.00 / $6.00
- Context64K
Mistral AI
Mixtral 8x7B
37/100- ECI118.5
- Price$0.70 / $0.70
- Context32K
- Our pick
OpenAI
GPT-4o
43/100- ECI129.0
- Price$2.50 / $10.00
- Context128K
GPT-4o is our pick
GPT-4o is the better all-round choice, scoring 43/100 against Mixtral 8x7B (37) and Mixtral 8x22B (33). It leads on capability, inputs & features and context window. Mixtral 8x7B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGPT-4oCapabilities Index (ECI): GPT-4o 129.0 · Mixtral 8x22B 122.0 · Mixtral 8x7B 118.5
- Lowest priceMixtral 8x7BMixtral 8x7B $0.70 · Mixtral 8x22B $3.00 · GPT-4o $4.38 per 1M tokens (3:1 blend)
- Longest contextGPT-4oGPT-4o 128,000 · Mixtral 8x22B 64,000 · Mixtral 8x7B 32,000 tokens
- Widest inputsGPT-4oMixtral 8x22B: Text · Mixtral 8x7B: Text · GPT-4o: Text, Images, PDFs
- Self-hostingMixtral 8x22B and Mixtral 8x7BPublishes downloadable weights
| Measure | Weight | Mixtral 8x22B | Mixtral 8x7B | GPT-4o |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 43 | 38 | 52 |
| Price | 25% | 27 | 57 | 19 |
| Inputs & features | 15% | 25 | 25 | 70 |
| Context window | 10% | 12 | 0 | 24 |
| Overall | 100% | 33/100 | 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) | 122.0 | 118.5 | 129.0 (best) |
| ECI rank | #139 of 148 | #142 of 148 | #129 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 34.1% | 30.6% | 48.9% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | — | — | 6.3% |
| Price per million tokens | |||
| Input | $2.00 | $0.70 (best) | $2.50 |
| Output | $6.00 | $0.70 (best) | $10.00 |
| Cached input | — | — | $1.25 |
| Blended (3:1) | $3.00 | $0.70 (best) | $4.38 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Mistral API | Official Mistral API | Official OpenAI API |
| Limits | |||
| Context window | 64,000 tokens | 32,000 tokens | 128,000 tokens (best) |
| Max output | 64,000 tokens (best) | 32,000 tokens | 16,384 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | 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 | No | Yes |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | open-mixtral-8x22b | open-mixtral-8x7b | gpt-4o |
| API providers | 1 | 1 | 19 (best) |
| Released | Apr 17, 2024 | Dec 11, 2023 | May 13, 2024 |
| Knowledge cutoff | Apr 2024 | Jan 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
Mixtral 8x7B$8.40
GPT-4o$45.00
Which should you choose?
Which is better: Mixtral 8x22B, Mixtral 8x7B or GPT-4o?
GPT-4o is the better all-round choice, scoring 43/100 against Mixtral 8x7B (37) and Mixtral 8x22B (33). It leads on capability, inputs & features and context window. Mixtral 8x7B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Mixtral 8x22B, Mixtral 8x7B or GPT-4o?
Mixtral 8x7B is cheaper at $0.70 input / $0.70 output per million tokens (official Mistral API price). 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 $0.70 per million tokens for Mixtral 8x7B versus $3.00 for Mixtral 8x22B (4.3× as much) and $4.38 for GPT-4o (6.3× as much).
Which scores higher on benchmarks?
GPT-4o scores higher on the Capabilities Index (ECI): GPT-4o 129.0 (#129 of 148), Mixtral 8x22B 122.0 (#139 of 148) and Mixtral 8x7B 118.5 (#142 of 148). The confidence ranges of the top two overlap (124.2–131.5 vs 115.1–124.4), so treat the gap as small. On individual benchmarks: GPQA Diamond — GPT-4o 48.9%, Mixtral 8x22B 34.1%, Mixtral 8x7B 30.6%.
Which is better for coding?
There are no published SWE-bench Verified results for Mixtral 8x22B, Mixtral 8x7B 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?
GPT-4o has the largest context window at 128,000 tokens, against 64,000 for Mixtral 8x22B and 32,000 for Mixtral 8x7B. Maximum output per response: Mixtral 8x22B up to 64,000, Mixtral 8x7B up to 32,000, GPT-4o up to 16,384 tokens.
Which can read images, PDFs, audio or video?
Mixtral 8x22B accepts text; Mixtral 8x7B accepts text; GPT-4o accepts text, images and PDFs. GPT-4o handles the widest range of inputs.
Are any of these open source?
Mixtral 8x22B and Mixtral 8x7B publishes its weights and can be self-hosted; GPT-4o is proprietary.
Which is newer?
GPT-4o is the newest, released May 13, 2024. Mixtral 8x22B came out Apr 17, 2024; Mixtral 8x7B came out Dec 11, 2023. Knowledge cutoff: Mixtral 8x22B Apr 2024, Mixtral 8x7B Jan 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.