ZMIME
Comparison · 3 models · Updated Nov 2, 2026

Mistral 7B Instruct v0.3 vs Mistral Large vs Llama-3.1-8B-Instruct

Mistral Large comes out ahead, 40 to 32 and 22 on our weighted score, though Llama-3.1-8B-Instruct is 12× cheaper per token.

  1. Mistral AI

    Mistral 7B Instruct v0.3

    Released May 22, 2024

    22/100
    • ECI109.0
    • Price—
    • Context33K
  2. Our pick

    Mistral AI

    Mistral Large

    Released Feb 26, 2024

    40/100
    • ECI122.0
    • Price$0.50 / $1.50
    • Context128K
  3. Meta

    Llama-3.1-8B-Instruct

    Released Jul 23, 2024

    32/100
    • ECI116.4
    • Price$0.06 / $0.08
    • Context128K
01 — Verdict

Mistral Large is our pick

Mistral Large is the better all-round choice, scoring 40/100 against Llama-3.1-8B-Instruct (32) and Mistral 7B Instruct v0.3 (22). It leads on capability and inputs & features. The score weighs capability 67%, inputs & features 20%, context window 13%.

  • CapabilityMistral LargeCapabilities Index (ECI): Mistral Large 122.0 · Llama-3.1-8B-Instruct 116.4 · Mistral 7B Instruct v0.3 109.0
  • Lowest priceLlama-3.1-8B-InstructLlama-3.1-8B-Instruct $0.065 · Mistral Large $0.75 per 1M tokens (3:1 blend) · Mistral 7B Instruct v0.3 unpriced
  • Longest contextMistral Large and Llama-3.1-8B-InstructMistral Large 128,000 · Llama-3.1-8B-Instruct 128,000 · Mistral 7B Instruct v0.3 32,768 tokens
  • Widest inputsMistral LargeMistral 7B Instruct v0.3: Text · Mistral Large: Text, PDFs · Llama-3.1-8B-Instruct: Text
  • Self-hostingMistral 7B Instruct v0.3 and Llama-3.1-8B-InstructPublishes downloadable weights (Apache 2.0)
How the score is built
MeasureWeightMistral 7B Instruct v0.3Mistral LargeLlama-3.1-8B-Instruct
CapabilityCapabilities Index (ECI)67%264235
Inputs & features20%254525
Context window13%02424
Overall100%22/10040/10032/100

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.

Mistral 7B Instruct v0.3 vs Mistral Large vs Llama-3.1-8B-Instruct specifications side by side
SpecificationMistral 7B Instruct v0.3Mistral AIMistral LargeMistral AILlama-3.1-8B-InstructMeta
Capability
Capabilities Index (ECI)109.0122.0 (best)116.4
ECI rank#164 of 165#153 of 165 (best)#162 of 165
GPQA DiamondGraduate-level science questions15.2%38.8% (best)27.0%
OTIS Mock AIME 2024–2025Competition mathematics0.3%1.9% (best)1.7%
Price per million tokens
Input—$0.50$0.06 (best)
Output—$1.50$0.08 (best)
Cached input—$0.05—
Blended (3:1)—$0.75$0.065 (best)
Long-context rate—Same rateSame rate
Price source—Official Mistral APIMedian of 17 providers
Limits
Context window32,768 tokens128,000 tokens (best)128,000 tokens (best)
Max output32,768 tokens102,400 tokens (best)4,096 tokens
Inputs and features
TextYesYesYes
ImagesNoNoNo
PDFsNoYesNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingYesYesYes
Structured outputNoYesNo
Availability
WeightsOpenApache 2.0ProprietaryOpen
API model ID—mistral-large-latest—
API providers11118 (best)
ReleasedMay 22, 2024Feb 26, 2024Jul 23, 2024
Knowledge cutoff—Nov 30, 2024Dec 2023
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.

  • Mistral 7B Instruct v0.3—
  • Mistral Large$8.00
  • Llama-3.1-8B-Instruct$0.76
04 — Questions

Which should you choose?

Which is better: Mistral 7B Instruct v0.3, Mistral Large or Llama-3.1-8B-Instruct?

Mistral Large is the better all-round choice, scoring 40/100 against Llama-3.1-8B-Instruct (32) and Mistral 7B Instruct v0.3 (22). It leads on capability and inputs & features. The score weighs capability 67%, inputs & features 20%, context window 13%.

Which is cheaper, Mistral 7B Instruct v0.3, Mistral Large or Llama-3.1-8B-Instruct?

Llama-3.1-8B-Instruct is cheaper at $0.06 input / $0.08 output per million tokens (median across 17 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 $0.065 per million tokens for Llama-3.1-8B-Instruct versus $0.75 for Mistral Large (12× as much). Mistral 7B Instruct v0.3 has no published per-token price.

Which scores higher on benchmarks?

Mistral Large scores higher on the Capabilities Index (ECI): Mistral Large 122.0 (#153 of 165), Llama-3.1-8B-Instruct 116.4 (#162 of 165) and Mistral 7B Instruct v0.3 109.0 (#164 of 165). The confidence ranges of the top two overlap (115.7–124.8 vs 107.0–121.6), so treat the gap as small. On individual benchmarks: GPQA Diamond — Mistral Large 38.8%, Llama-3.1-8B-Instruct 27.0%, Mistral 7B Instruct v0.3 15.2%; OTIS Mock AIME 2024–2025 — Mistral Large 1.9%, Llama-3.1-8B-Instruct 1.7%, Mistral 7B Instruct v0.3 0.3%.

Which is better for coding?

There are no published SWE-bench Verified results for Mistral 7B Instruct v0.3, Mistral Large and Llama-3.1-8B-Instruct yet, so there is no like-for-like coding score. On overall capability, Mistral Large leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.

Which has the bigger context window?

Mistral Large and Llama-3.1-8B-Instruct have the largest context windows (128,000 and 128,000 tokens), against 32,768 for Mistral 7B Instruct v0.3. Maximum output per response: Mistral 7B Instruct v0.3 up to 32,768, Mistral Large up to 102,400, Llama-3.1-8B-Instruct up to 4,096 tokens.

Which can read images, PDFs, audio or video?

Mistral 7B Instruct v0.3 accepts text; Mistral Large accepts text and PDFs; Llama-3.1-8B-Instruct accepts text. Mistral Large handles the widest range of inputs.

Are any of these open source?

Mistral 7B Instruct v0.3 and Llama-3.1-8B-Instruct publishes its weights (Apache 2.0) and can be self-hosted; Mistral Large is proprietary.

Which is newer?

Llama-3.1-8B-Instruct is the newest, released Jul 23, 2024. Mistral 7B Instruct v0.3 came out May 22, 2024; Mistral Large came out Feb 26, 2024. Knowledge cutoff: Mistral Large Nov 30, 2024, Llama-3.1-8B-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.