Mixtral 8x22B Instruct vs Llama-3.2-90B-Vision-Instruct
Llama-3.2-90B-Vision-Instruct comes out ahead, 44 to 37 on our weighted score.
Mistral AIMixtral 8x22B Instruct
37/100- ECI122.0
- Price$2.00 / $6.00
- Context66K
- Our pick
MetaLlama-3.2-90B-Vision-Instruct
44/100- ECI125.5
- Price—
- Context128K
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Make it a three-way comparison.
Llama-3.2-90B-Vision-Instruct is our pick
Llama-3.2-90B-Vision-Instruct is the better all-round choice, scoring 44/100 against Mixtral 8x22B Instruct (37). It leads on capability, inputs & features and context window. The score weighs capability 67%, inputs & features 20%, context window 13%.
- CapabilityLlama-3.2-90B-Vision-InstructCapabilities Index (ECI): Llama-3.2-90B-Vision-Instruct 125.5 · Mixtral 8x22B Instruct 122.0
- Lowest priceMixtral 8x22B InstructMixtral 8x22B Instruct $3.00 per 1M tokens (3:1 blend) · Llama-3.2-90B-Vision-Instruct unpriced
- Longest contextLlama-3.2-90B-Vision-InstructLlama-3.2-90B-Vision-Instruct 128,000 · Mixtral 8x22B Instruct 65,536 tokens
- Widest inputsSame inputsMixtral 8x22B Instruct: Text, PDFs · Llama-3.2-90B-Vision-Instruct: Text, Images
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Mixtral 8x22B Instruct | Llama-3.2-90B-Vision-Instruct |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 67% | 42 | 46 |
| Inputs & features | 20% | 35 | 50 |
| Context window | 13% | 12 | 24 |
| Overall | 100% | 37/100 | 44/100 |
Left out because at least one model lacks the data: price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Mixtral 8x22B InstructMistral AI | Llama-3.2-90B-Vision-InstructMeta |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 122.0 | 125.5 (best) |
| ECI rank | #155 of 165 | #150 of 165 (best) |
| GPQA DiamondGraduate-level science questions | 34.1% | 41.0% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 2.6% |
| Price per million tokens | ||
| Input | $2.00 | — |
| Output | $6.00 | — |
| Cached input | — | — |
| Blended (3:1) | $3.00 | — |
| Long-context rate | Same rate | — |
| Price source | Median of 5 providers | — |
| Limits | ||
| Context window | 65,536 tokens | 128,000 tokens (best) |
| Max output | 52,428 tokens (best) | 4,096 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | Yes |
| PDFs | Yes | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Open | OpenLlama 3.2 Community License |
| API model ID | — | — |
| API providers | 5 (best) | 1 |
| Released | Apr 17, 2024 | Sep 25, 2024 |
| Knowledge cutoff | Jan 31, 2024 | Dec 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 Instruct$32.00
- Llama-3.2-90B-Vision-Instruct—
Which should you choose?
Which is better: Mixtral 8x22B Instruct or Llama-3.2-90B-Vision-Instruct?
Llama-3.2-90B-Vision-Instruct is the better all-round choice, scoring 44/100 against Mixtral 8x22B Instruct (37). It leads on capability, inputs & features and context window. The score weighs capability 67%, inputs & features 20%, context window 13%.
Which is cheaper, Mixtral 8x22B Instruct or Llama-3.2-90B-Vision-Instruct?
Mixtral 8x22B Instruct is cheaper at $2.00 input / $6.00 output per million tokens (median across 5 API providers). . At a typical mix of three input tokens to one output token, that is $3.00 per million tokens for Mixtral 8x22B Instruct versus . Llama-3.2-90B-Vision-Instruct has no published per-token price.
Which scores higher on benchmarks?
Llama-3.2-90B-Vision-Instruct scores higher on the Capabilities Index (ECI): Llama-3.2-90B-Vision-Instruct 125.5 (#150 of 165) and Mixtral 8x22B Instruct 122.0 (#155 of 165). The confidence ranges of the top two overlap (120.3–127.4 vs 115.7–124.3), so treat the gap as small. On individual benchmarks: GPQA Diamond — Llama-3.2-90B-Vision-Instruct 41.0%, Mixtral 8x22B Instruct 34.1%.
Which is better for coding?
There are no published SWE-bench Verified results for Mixtral 8x22B Instruct and Llama-3.2-90B-Vision-Instruct yet, so there is no like-for-like coding score. On overall capability, Llama-3.2-90B-Vision-Instruct leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.
Which has the bigger context window?
Llama-3.2-90B-Vision-Instruct has the largest context window at 128,000 tokens, against 65,536 for Mixtral 8x22B Instruct. Maximum output per response: Mixtral 8x22B Instruct up to 52,428, Llama-3.2-90B-Vision-Instruct up to 4,096 tokens.
Which can read images, PDFs, audio or video?
Mixtral 8x22B Instruct accepts text and PDFs; Llama-3.2-90B-Vision-Instruct accepts text and images. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights (Llama 3.2 Community License), so you can self-host them.
Which is newer?
Llama-3.2-90B-Vision-Instruct is the newest, released Sep 25, 2024. Mixtral 8x22B Instruct came out Apr 17, 2024. Knowledge cutoff: Mixtral 8x22B Instruct Jan 31, 2024, Llama-3.2-90B-Vision-Instruct Dec 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 Nov 2, 2026.
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