ZMIME
Comparison · 3 models · Updated Oct 4, 2026

Mistral Nemo vs Llama 4 Scout 17B Instruct vs Llama-3.1-8B-Instruct

Llama 4 Scout 17B Instruct comes out ahead, 62 to 48 and 46 on our weighted score, though Mistral Nemo is 2.3× cheaper per token.

  1. Mistral AI

    Mistral Nemo

    Released Jul 1, 2024

    48/100
    • ECI118.7
    • Price$0.15 / $0.15
    • Context128K
  2. Our pick

    Meta

    Llama 4 Scout 17B Instruct

    Released Apr 5, 2025

    62/100
    • ECI129.7
    • Price$0.225 / $0.69
    • Context10M
  3. Meta

    Llama-3.1-8B-Instruct

    Released Jul 23, 2024

    46/100
    • ECI116.6
    • Price$0.152 / $0.167
    • Context128K
01 — Verdict

Llama 4 Scout 17B Instruct is our pick

Llama 4 Scout 17B Instruct is the better all-round choice, scoring 62/100 against Mistral Nemo (48) and Llama-3.1-8B-Instruct (46). It leads on capability, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityLlama 4 Scout 17B InstructCapabilities Index (ECI): Llama 4 Scout 17B Instruct 129.7 · Mistral Nemo 118.7 · Llama-3.1-8B-Instruct 116.6
  • Lowest priceMistral NemoMistral Nemo $0.15 · Llama-3.1-8B-Instruct $0.156 · Llama 4 Scout 17B Instruct $0.341 per 1M tokens (3:1 blend)
  • Longest contextLlama 4 Scout 17B InstructLlama 4 Scout 17B Instruct 10,000,000 · Mistral Nemo 128,000 · Llama-3.1-8B-Instruct 128,000 tokens
  • Widest inputsLlama 4 Scout 17B InstructMistral Nemo: Text · Llama 4 Scout 17B Instruct: Text, Images · Llama-3.1-8B-Instruct: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightMistral NemoLlama 4 Scout 17B InstructLlama-3.1-8B-Instruct
CapabilityCapabilities Index (ECI)50%395236
Price25%897288
Inputs & features15%255025
Context window10%2410024
Overall100%48/10062/10046/100
02 — Side by side

Every spec in one table

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

Mistral Nemo vs Llama 4 Scout 17B Instruct vs Llama-3.1-8B-Instruct specifications side by side
SpecificationMistral NemoMistral AILlama 4 Scout 17B InstructMetaLlama-3.1-8B-InstructMeta
Capability
Capabilities Index (ECI)118.7129.7 (best)116.6
ECI rank#140 of 148#126 of 148 (best)#145 of 148
GPQA DiamondGraduate-level science questions29.9%51.8% (best)27.0%
OTIS Mock AIME 2024–2025Competition mathematics—7.8% (best)1.7%
Price per million tokens
Input$0.15 (best)$0.225$0.152
Output$0.15 (best)$0.69$0.167
Cached input———
Blended (3:1)$0.15 (best)$0.341$0.156
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Mistral APIMedian of 4 providersMedian of 9 providers
Limits
Context window128,000 tokens10,000,000 tokens (best)128,000 tokens
Max output128,000 tokens (best)16,384 tokens4,096 tokens
Inputs and features
TextYesYesYes
ImagesNoYesNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsOpenOpenOpen
API model IDmistral-nemo——
API providers549 (best)
ReleasedJul 1, 2024Apr 5, 2025Jul 23, 2024
Knowledge cutoffJul 2024Aug 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 Nemo$1.80
  • Llama 4 Scout 17B Instruct$3.63
  • Llama-3.1-8B-Instruct$1.85
04 — Questions

Which should you choose?

Which is better: Mistral Nemo, Llama 4 Scout 17B Instruct or Llama-3.1-8B-Instruct?

Llama 4 Scout 17B Instruct is the better all-round choice, scoring 62/100 against Mistral Nemo (48) and Llama-3.1-8B-Instruct (46). It leads on capability, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Mistral Nemo, Llama 4 Scout 17B Instruct or Llama-3.1-8B-Instruct?

Mistral Nemo is cheaper at $0.15 input / $0.15 output per million tokens (official Mistral API price). Llama-3.1-8B-Instruct costs $0.152 input / $0.167 output per million tokens (median across 9 API providers); Llama 4 Scout 17B Instruct costs $0.225 input / $0.69 output per million tokens (median across 4 API providers). At a typical mix of three input tokens to one output token, that is $0.15 per million tokens for Mistral Nemo versus $0.156 for Llama-3.1-8B-Instruct (1× as much) and $0.341 for Llama 4 Scout 17B Instruct (2.3× as much).

Which scores higher on benchmarks?

Llama 4 Scout 17B Instruct scores higher on the Capabilities Index (ECI): Llama 4 Scout 17B Instruct 129.7 (#126 of 148), Mistral Nemo 118.7 (#140 of 148) and Llama-3.1-8B-Instruct 116.6 (#145 of 148). Their confidence ranges do not overlap (124.8–131.4 vs 111.3–121.5), so the gap is a real one. On individual benchmarks: GPQA Diamond — Llama 4 Scout 17B Instruct 51.8%, Mistral Nemo 29.9%, Llama-3.1-8B-Instruct 27.0%.

Which is better for coding?

There are no published SWE-bench Verified results for Mistral Nemo, Llama 4 Scout 17B Instruct and Llama-3.1-8B-Instruct yet, so there is no like-for-like coding score. On overall capability, Llama 4 Scout 17B Instruct 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?

Llama 4 Scout 17B Instruct has the largest context window at 10,000,000 tokens, against 128,000 for Mistral Nemo and 128,000 for Llama-3.1-8B-Instruct. Maximum output per response: Mistral Nemo up to 128,000, Llama 4 Scout 17B Instruct up to 16,384, Llama-3.1-8B-Instruct up to 4,096 tokens.

Which can read images, PDFs, audio or video?

Mistral Nemo accepts text; Llama 4 Scout 17B Instruct accepts text and images; Llama-3.1-8B-Instruct accepts text. Llama 4 Scout 17B Instruct handles the widest range of inputs.

Are any of these open source?

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

Which is newer?

Llama 4 Scout 17B Instruct is the newest, released Apr 5, 2025. Llama-3.1-8B-Instruct came out Jul 23, 2024; Mistral Nemo came out Jul 1, 2024. Knowledge cutoff: Mistral Nemo Jul 2024, Llama 4 Scout 17B Instruct Aug 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 Oct 4, 2026.