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Comparison · 2 models · Updated Nov 2, 2026

Llama-3.2-90B-Vision-Instruct vs Mistral Large 2407

Too close to call on our weighted score (Llama-3.2-90B-Vision-Instruct 44, Mistral Large 2407 43). The right pick depends on what you value most.

  1. Meta

    Llama-3.2-90B-Vision-Instruct

    Released Sep 25, 2024

    44/100
    • ECI125.5
    • Price—
    • Context128K
    Full specs Remove Llama-3.2-90B-Vision-Instruct

  2. Mistral AI

    Mistral Large 2407

    Released Jul 24, 2024

    43/100
    • ECI127.6
    • Price$2.00 / $6.00
    • Context131K
    Full specs Remove Mistral Large 2407

  3. Add a model

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01 — Verdict

Too close to call

It is close. Our weighted score puts them within 1 points (Llama-3.2-90B-Vision-Instruct 44/100, Mistral Large 2407 43/100), so choose by what matters most for your work: Mistral Large 2407 for raw capability. The score weighs capability 67%, inputs & features 20%, context window 13%.

  • CapabilityMistral Large 2407Capabilities Index (ECI): Mistral Large 2407 127.6 · Llama-3.2-90B-Vision-Instruct 125.5
  • Lowest priceMistral Large 2407Mistral Large 2407 $3.00 per 1M tokens (3:1 blend) · Llama-3.2-90B-Vision-Instruct unpriced
  • Longest contextMistral Large 2407Mistral Large 2407 131,072 · Llama-3.2-90B-Vision-Instruct 128,000 tokens
  • Widest inputsSame inputsLlama-3.2-90B-Vision-Instruct: Text, Images · Mistral Large 2407: Text, PDFs
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightLlama-3.2-90B-Vision-InstructMistral Large 2407
CapabilityCapabilities Index (ECI)67%4649
Inputs & features20%5035
Context window13%2425
Overall100%44/10043/100

Left out because at least one model lacks the data: price. The remaining weights were rescaled.

02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

Llama-3.2-90B-Vision-Instruct vs Mistral Large 2407 specifications side by side
SpecificationLlama-3.2-90B-Vision-InstructMetaMistral Large 2407Mistral AI
Capability
Capabilities Index (ECI)125.5127.6 (best)
ECI rank#150 of 165#144 of 165 (best)
GPQA DiamondGraduate-level science questions41.0%49.0% (best)
OTIS Mock AIME 2024–2025Competition mathematics2.6%8.5% (best)
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 window128,000 tokens131,072 tokens (best)
Max output4,096 tokens104,857 tokens (best)
Inputs and features
TextYesYes
ImagesYesNo
PDFsNoYes
AudioNoNo
VideoNoNo
ReasoningNoNo
Tool callingYesYes
Structured outputNoNo
Availability
WeightsOpenLlama 3.2 Community LicenseOpen
API model ID——
API providers15 (best)
ReleasedSep 25, 2024Jul 24, 2024
Knowledge cutoffDec 2023Mar 31, 2024
03 — Cost

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 2407$32.00
04 — Questions

Which should you choose?

Which is better: Llama-3.2-90B-Vision-Instruct or Mistral Large 2407?

It is close. Our weighted score puts them within 1 points (Llama-3.2-90B-Vision-Instruct 44/100, Mistral Large 2407 43/100), so choose by what matters most for your work: Mistral Large 2407 for raw capability. The score weighs capability 67%, inputs & features 20%, context window 13%.

Which is cheaper, Llama-3.2-90B-Vision-Instruct or Mistral Large 2407?

Mistral Large 2407 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 Mistral Large 2407 versus . Llama-3.2-90B-Vision-Instruct has no published per-token price.

Which scores higher on benchmarks?

Mistral Large 2407 scores higher on the Capabilities Index (ECI): Mistral Large 2407 127.6 (#144 of 165) and Llama-3.2-90B-Vision-Instruct 125.5 (#150 of 165). The confidence ranges of the top two overlap (123.3–129.4 vs 120.3–127.4), so treat the gap as small. On individual benchmarks: GPQA Diamond — Mistral Large 2407 49.0%, Llama-3.2-90B-Vision-Instruct 41.0%; OTIS Mock AIME 2024–2025 — Mistral Large 2407 8.5%, Llama-3.2-90B-Vision-Instruct 2.6%.

Which is better for coding?

There are no published SWE-bench Verified results for Llama-3.2-90B-Vision-Instruct and Mistral Large 2407 yet, so there is no like-for-like coding score. On overall capability, Mistral Large 2407 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?

Mistral Large 2407 has the largest context window at 131,072 tokens, against 128,000 for Llama-3.2-90B-Vision-Instruct. Maximum output per response: Llama-3.2-90B-Vision-Instruct up to 4,096, Mistral Large 2407 up to 104,857 tokens.

Which can read images, PDFs, audio or video?

Llama-3.2-90B-Vision-Instruct accepts text and images; Mistral Large 2407 accepts text and PDFs. 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. Mistral Large 2407 came out Jul 24, 2024. Knowledge cutoff: Llama-3.2-90B-Vision-Instruct Dec 2023, Mistral Large 2407 Mar 31, 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.

05 — Keep comparing

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