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Comparison · 2 models · Updated Nov 2, 2026

Llama-3.1-70B-Instruct vs Mistral Large

Too close to call on our weighted score (Mistral Large 44, Llama-3.1-70B-Instruct 43). The right pick depends on what you value most.

  1. Meta

    Llama-3.1-70B-Instruct

    Released Jul 23, 2024

    43/100
    • ECI125.9
    • Price$0.72 / $0.72
    • Context128K
    Full specs Remove Llama-3.1-70B-Instruct

  2. Mistral AI

    Mistral Large

    Released Feb 26, 2024

    44/100
    • ECI122.0
    • Price$0.50 / $1.50
    • Context128K
    Full specs Remove Mistral Large

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01 — Verdict

Too close to call

It is close. Our weighted score puts them within a point (Mistral Large 44/100, Llama-3.1-70B-Instruct 43/100), so choose by what matters most for your work: Llama-3.1-70B-Instruct for raw capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityLlama-3.1-70B-InstructCapabilities Index (ECI): Llama-3.1-70B-Instruct 125.9 · Mistral Large 122.0
  • Lowest priceLlama-3.1-70B-InstructLlama-3.1-70B-Instruct $0.72 · Mistral Large $0.75 per 1M tokens (3:1 blend)
  • Longest contextAbout the sameLlama-3.1-70B-Instruct 128,000 · Mistral Large 128,000 tokens
  • Widest inputsMistral LargeLlama-3.1-70B-Instruct: Text · Mistral Large: Text, PDFs
  • Self-hostingLlama-3.1-70B-InstructPublishes downloadable weights
How the score is built
MeasureWeightLlama-3.1-70B-InstructMistral Large
CapabilityCapabilities Index (ECI)50%4742
Price25%5453
Inputs & features15%2545
Context window10%2424
Overall100%43/10044/100
02 — Side by side

Every spec in one table

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

Llama-3.1-70B-Instruct vs Mistral Large specifications side by side
SpecificationLlama-3.1-70B-InstructMetaMistral LargeMistral AI
Capability
Capabilities Index (ECI)125.9 (best)122.0
ECI rank#149 of 165 (best)#153 of 165
GPQA DiamondGraduate-level science questions44.2% (best)38.8%
OTIS Mock AIME 2024–2025Competition mathematics3.6% (best)1.9%
Price per million tokens
Input$0.72$0.50 (best)
Output$0.72 (best)$1.50
Cached input—$0.05
Blended (3:1)$0.72 (best)$0.75
Long-context rateSame rateSame rate
Price sourceMedian of 8 providersOfficial Mistral API
Limits
Context window128,000 tokens128,000 tokens
Max output4,096 tokens102,400 tokens (best)
Inputs and features
TextYesYes
ImagesNoNo
PDFsNoYes
AudioNoNo
VideoNoNo
ReasoningNoNo
Tool callingYesYes
Structured outputNoYes
Availability
WeightsOpenProprietary
API model ID—mistral-large-latest
API providers811 (best)
ReleasedJul 23, 2024Feb 26, 2024
Knowledge cutoffDec 2023Nov 30, 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-3.1-70B-Instruct$8.64
  • Mistral Large$8.00
04 — Questions

Which should you choose?

Which is better: Llama-3.1-70B-Instruct or Mistral Large?

It is close. Our weighted score puts them within a point (Mistral Large 44/100, Llama-3.1-70B-Instruct 43/100), so choose by what matters most for your work: Llama-3.1-70B-Instruct for raw capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Llama-3.1-70B-Instruct or Mistral Large?

Llama-3.1-70B-Instruct is cheaper at $0.72 input / $0.72 output per million tokens (median across 8 API providers). Mistral Large costs $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 $0.72 per million tokens for Llama-3.1-70B-Instruct versus $0.75 for Mistral Large (1× as much).

Which scores higher on benchmarks?

Llama-3.1-70B-Instruct scores higher on the Capabilities Index (ECI): Llama-3.1-70B-Instruct 125.9 (#149 of 165) and Mistral Large 122.0 (#153 of 165). The confidence ranges of the top two overlap (120.8–128.2 vs 115.7–124.8), so treat the gap as small. On individual benchmarks: GPQA Diamond — Llama-3.1-70B-Instruct 44.2%, Mistral Large 38.8%; OTIS Mock AIME 2024–2025 — Llama-3.1-70B-Instruct 3.6%, Mistral Large 1.9%.

Which is better for coding?

There are no published SWE-bench Verified results for Llama-3.1-70B-Instruct and Mistral Large yet, so there is no like-for-like coding score. On overall capability, Llama-3.1-70B-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-3.1-70B-Instruct and Mistral Large share the same 128,000-token context window. Maximum output per response: Llama-3.1-70B-Instruct up to 4,096, Mistral Large up to 102,400 tokens.

Which can read images, PDFs, audio or video?

Llama-3.1-70B-Instruct accepts text; Mistral Large accepts text and PDFs. Mistral Large handles the widest range of inputs.

Are any of these open source?

Llama-3.1-70B-Instruct publishes its weights and can be self-hosted; Mistral Large is proprietary.

Which is newer?

Llama-3.1-70B-Instruct is the newest, released Jul 23, 2024. Mistral Large came out Feb 26, 2024. Knowledge cutoff: Llama-3.1-70B-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.

05 — Keep comparing

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