Llama-3.2-90B-Vision-Instruct vs Mistral Large
Llama-3.2-90B-Vision-Instruct comes out ahead, 44 to 40 on our weighted score.
- Our pick
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Llama-3.2-90B-Vision-Instruct
44/100- ECI125.5
- Price—
- Context128K
Mistral AI
Mistral Large
40/100- ECI122.0
- Price$0.50 / $1.50
- Context128K
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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 Mistral Large (40). It leads on capability and inputs & features. 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 · Mistral Large 122.0
- Lowest priceMistral LargeMistral Large $0.75 per 1M tokens (3:1 blend) · Llama-3.2-90B-Vision-Instruct unpriced
- Longest contextAbout the sameLlama-3.2-90B-Vision-Instruct 128,000 · Mistral Large 128,000 tokens
- Widest inputsSame inputsLlama-3.2-90B-Vision-Instruct: Text, Images · Mistral Large: Text, PDFs
- Self-hostingLlama-3.2-90B-Vision-InstructPublishes downloadable weights (Llama 3.2 Community License)
| Measure | Weight | Llama-3.2-90B-Vision-Instruct | Mistral Large |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 67% | 46 | 42 |
| Inputs & features | 20% | 50 | 45 |
| Context window | 13% | 24 | 24 |
| Overall | 100% | 44/100 | 40/100 |
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 | ||
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 125.5 (best) | 122.0 |
| ECI rank | #150 of 165 (best) | #153 of 165 |
| GPQA DiamondGraduate-level science questions | 41.0% (best) | 38.8% |
| OTIS Mock AIME 2024–2025Competition mathematics | 2.6% (best) | 1.9% |
| Price per million tokens | ||
| Input | — | $0.50 |
| Output | — | $1.50 |
| Cached input | — | $0.05 |
| Blended (3:1) | — | $0.75 |
| Long-context rate | — | Same rate |
| Price source | — | Official Mistral API |
| Limits | ||
| Context window | 128,000 tokens | 128,000 tokens |
| Max output | 4,096 tokens | 102,400 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | No |
| PDFs | No | Yes |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | Yes |
| Structured output | No | Yes |
| Availability | ||
| Weights | OpenLlama 3.2 Community License | Proprietary |
| API model ID | — | mistral-large-latest |
| API providers | 1 | 11 (best) |
| Released | Sep 25, 2024 | Feb 26, 2024 |
| Knowledge cutoff | Dec 2023 | Nov 30, 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
Llama-3.2-90B-Vision-Instruct—
Mistral Large$8.00
Which should you choose?
Which is better: Llama-3.2-90B-Vision-Instruct or Mistral Large?
Llama-3.2-90B-Vision-Instruct is the better all-round choice, scoring 44/100 against Mistral Large (40). It leads on capability and inputs & features. The score weighs capability 67%, inputs & features 20%, context window 13%.
Which is cheaper, Llama-3.2-90B-Vision-Instruct or Mistral Large?
Mistral Large is cheaper at $0.50 input / $1.50 output per million tokens (official Mistral API price). . At a typical mix of three input tokens to one output token, that is $0.75 per million tokens for Mistral Large 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 Mistral Large 122.0 (#153 of 165). The confidence ranges of the top two overlap (120.3–127.4 vs 115.7–124.8), so treat the gap as small. On individual benchmarks: GPQA Diamond — Llama-3.2-90B-Vision-Instruct 41.0%, Mistral Large 38.8%; OTIS Mock AIME 2024–2025 — Llama-3.2-90B-Vision-Instruct 2.6%, Mistral Large 1.9%.
Which is better for coding?
There are no published SWE-bench Verified results for Llama-3.2-90B-Vision-Instruct and Mistral Large 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 and Mistral Large share the same 128,000-token context window. Maximum output per response: Llama-3.2-90B-Vision-Instruct up to 4,096, Mistral Large up to 102,400 tokens.
Which can read images, PDFs, audio or video?
Llama-3.2-90B-Vision-Instruct accepts text and images; Mistral Large accepts text and PDFs. They handle the same number of input types.
Are any of these open source?
Llama-3.2-90B-Vision-Instruct publishes its weights (Llama 3.2 Community License) and can be self-hosted; Mistral Large is proprietary.
Which is newer?
Llama-3.2-90B-Vision-Instruct is the newest, released Sep 25, 2024. Mistral Large came out Feb 26, 2024. Knowledge cutoff: Llama-3.2-90B-Vision-Instruct Dec 2023, Mistral Large Nov 30, 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 Nov 2, 2026.