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Comparison · 2 models · Updated Nov 2, 2026

Llama-3.1-70B-Instruct vs Mistral Large 2407

Llama-3.1-70B-Instruct comes out ahead, 43 to 39 on our weighted score, and it is the cheaper option too.

  1. Our pick

    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 2407

    Released Jul 24, 2024

    39/100
    • ECI127.6
    • Price$2.00 / $6.00
    • Context131K
    Full specs Remove Mistral Large 2407

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Llama-3.1-70B-Instruct is our pick

Llama-3.1-70B-Instruct is the better all-round choice, scoring 43/100 against Mistral Large 2407 (39). It leads on price. Mistral Large 2407 wins on capability and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityMistral Large 2407Capabilities Index (ECI): Mistral Large 2407 127.6 · Llama-3.1-70B-Instruct 125.9
  • Lowest priceLlama-3.1-70B-InstructLlama-3.1-70B-Instruct $0.72 · Mistral Large 2407 $3.00 per 1M tokens (3:1 blend)
  • Longest contextMistral Large 2407Mistral Large 2407 131,072 · Llama-3.1-70B-Instruct 128,000 tokens
  • Widest inputsMistral Large 2407Llama-3.1-70B-Instruct: Text · 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-3.1-70B-InstructMistral Large 2407
CapabilityCapabilities Index (ECI)50%4749
Price25%5426
Inputs & features15%2535
Context window10%2425
Overall100%43/10039/100
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 2407 specifications side by side
SpecificationLlama-3.1-70B-InstructMetaMistral Large 2407Mistral AI
Capability
Capabilities Index (ECI)125.9127.6 (best)
ECI rank#149 of 165#144 of 165 (best)
GPQA DiamondGraduate-level science questions44.2%49.0% (best)
OTIS Mock AIME 2024–2025Competition mathematics3.6%8.5% (best)
Price per million tokens
Input$0.72 (best)$2.00
Output$0.72 (best)$6.00
Cached input——
Blended (3:1)$0.72 (best)$3.00
Long-context rateSame rateSame rate
Price sourceMedian of 8 providersMedian of 5 providers
Limits
Context window128,000 tokens131,072 tokens (best)
Max output4,096 tokens104,857 tokens (best)
Inputs and features
TextYesYes
ImagesNoNo
PDFsNoYes
AudioNoNo
VideoNoNo
ReasoningNoNo
Tool callingYesYes
Structured outputNoNo
Availability
WeightsOpenOpen
API model ID——
API providers8 (best)5
ReleasedJul 23, 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-3.1-70B-Instruct$8.64
  • Mistral Large 2407$32.00
04 — Questions

Which should you choose?

Which is better: Llama-3.1-70B-Instruct or Mistral Large 2407?

Llama-3.1-70B-Instruct is the better all-round choice, scoring 43/100 against Mistral Large 2407 (39). It leads on price. Mistral Large 2407 wins on capability and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Llama-3.1-70B-Instruct or Mistral Large 2407?

Llama-3.1-70B-Instruct is cheaper at $0.72 input / $0.72 output per million tokens (median across 8 API providers). Mistral Large 2407 costs $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 $0.72 per million tokens for Llama-3.1-70B-Instruct versus $3.00 for Mistral Large 2407 (4.2× as much).

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-3.1-70B-Instruct 125.9 (#149 of 165). The confidence ranges of the top two overlap (123.3–129.4 vs 120.8–128.2), so treat the gap as small. On individual benchmarks: GPQA Diamond — Mistral Large 2407 49.0%, Llama-3.1-70B-Instruct 44.2%; OTIS Mock AIME 2024–2025 — Mistral Large 2407 8.5%, Llama-3.1-70B-Instruct 3.6%.

Which is better for coding?

There are no published SWE-bench Verified results for Llama-3.1-70B-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-3.1-70B-Instruct. Maximum output per response: Llama-3.1-70B-Instruct up to 4,096, Mistral Large 2407 up to 104,857 tokens.

Which can read images, PDFs, audio or video?

Llama-3.1-70B-Instruct accepts text; Mistral Large 2407 accepts text and PDFs. Mistral Large 2407 handles the widest range of inputs.

Are any of these open source?

Yes, both publish their weights, so you can self-host them.

Which is newer?

Mistral Large 2407 is the newest, released Jul 24, 2024. Llama-3.1-70B-Instruct came out Jul 23, 2024. Knowledge cutoff: Llama-3.1-70B-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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