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Comparison · 3 models · Updated Oct 4, 2026

GPT-4o mini vs Llama-3.1-8B-Instruct vs Mistral Nemo

GPT-4o mini comes out ahead, 56 to 48 and 46 on our weighted score, though Mistral Nemo is 43% cheaper per token.

  1. Our pick

    OpenAI

    GPT-4o mini

    Released Jul 18, 2024

    56/100
    • ECI126.6
    • Price$0.15 / $0.60
    • Context128K
    Full specs Remove GPT-4o mini

  2. Meta

    Llama-3.1-8B-Instruct

    Released Jul 23, 2024

    46/100
    • ECI116.6
    • Price$0.152 / $0.167
    • Context128K
    Full specs Remove Llama-3.1-8B-Instruct

  3. Mistral AI

    Mistral Nemo

    Released Jul 1, 2024

    48/100
    • ECI118.7
    • Price$0.15 / $0.15
    • Context128K
    Full specs Remove Mistral Nemo
01 — Verdict

GPT-4o mini is our pick

GPT-4o mini is the better all-round choice, scoring 56/100 against Mistral Nemo (48) and Llama-3.1-8B-Instruct (46). It leads on capability and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGPT-4o miniCapabilities Index (ECI): GPT-4o mini 126.6 · Mistral Nemo 118.7 · Llama-3.1-8B-Instruct 116.6
  • Lowest priceMistral NemoMistral Nemo $0.15 · Llama-3.1-8B-Instruct $0.156 · GPT-4o mini $0.263 per 1M tokens (3:1 blend)
  • Longest contextAbout the sameGPT-4o mini 128,000 · Llama-3.1-8B-Instruct 128,000 · Mistral Nemo 128,000 tokens
  • Widest inputsGPT-4o miniGPT-4o mini: Text, Images, PDFs · Llama-3.1-8B-Instruct: Text · Mistral Nemo: Text
  • Self-hostingLlama-3.1-8B-Instruct and Mistral NemoPublishes downloadable weights
How the score is built
MeasureWeightGPT-4o miniLlama-3.1-8B-InstructMistral Nemo
CapabilityCapabilities Index (ECI)50%493639
Price25%778889
Inputs & features15%702525
Context window10%242424
Overall100%56/10046/10048/100
02 — Side by side

Every spec in one table

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

GPT-4o mini vs Llama-3.1-8B-Instruct vs Mistral Nemo specifications side by side
SpecificationGPT-4o miniOpenAILlama-3.1-8B-InstructMetaMistral NemoMistral AI
Capability
Capabilities Index (ECI)126.6 (best)116.6118.7
ECI rank#135 of 148 (best)#145 of 148#140 of 148
GPQA DiamondGraduate-level science questions37.7% (best)27.0%29.9%
FrontierMath Tiers 1–3Research-level mathematics0.7%——
OTIS Mock AIME 2024–2025Competition mathematics6.9% (best)1.7%—
SimpleQA VerifiedShort factual questions8.3%——
Price per million tokens
Input$0.15 (best)$0.152$0.15 (best)
Output$0.60$0.167$0.15 (best)
Cached input$0.075——
Blended (3:1)$0.263$0.156$0.15 (best)
Long-context rateSame rateSame rateSame rate
Price sourceOfficial OpenAI APIMedian of 9 providersOfficial Mistral API
Limits
Context window128,000 tokens128,000 tokens128,000 tokens
Max output16,384 tokens4,096 tokens128,000 tokens (best)
Inputs and features
TextYesYesYes
ImagesYesNoNo
PDFsYesNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingYesYesYes
Structured outputYesNoNo
Availability
WeightsProprietaryOpenOpen
API model IDgpt-4o-mini—mistral-nemo
API providers21 (best)95
ReleasedJul 18, 2024Jul 23, 2024Jul 1, 2024
Knowledge cutoffSep 2023Dec 2023Jul 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.

  • GPT-4o mini$2.70
  • Llama-3.1-8B-Instruct$1.85
  • Mistral Nemo$1.80
04 — Questions

Which should you choose?

Which is better: GPT-4o mini, Llama-3.1-8B-Instruct or Mistral Nemo?

GPT-4o mini is the better all-round choice, scoring 56/100 against Mistral Nemo (48) and Llama-3.1-8B-Instruct (46). It leads on capability and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, GPT-4o mini, Llama-3.1-8B-Instruct or Mistral Nemo?

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); GPT-4o mini costs $0.15 input / $0.60 output per million tokens (official OpenAI API price). 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 $0.263 for GPT-4o mini (1.8× as much).

Which scores higher on benchmarks?

GPT-4o mini scores higher on the Capabilities Index (ECI): GPT-4o mini 126.6 (#135 of 148), Mistral Nemo 118.7 (#140 of 148) and Llama-3.1-8B-Instruct 116.6 (#145 of 148). The confidence ranges of the top two overlap (120.5–128.5 vs 111.3–121.5), so treat the gap as small. On individual benchmarks: GPQA Diamond — GPT-4o mini 37.7%, 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 GPT-4o mini, Llama-3.1-8B-Instruct and Mistral Nemo yet, so there is no like-for-like coding score. On overall capability, GPT-4o mini 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?

GPT-4o mini, Llama-3.1-8B-Instruct and Mistral Nemo share the same 128,000-token context window. Maximum output per response: GPT-4o mini up to 16,384, Llama-3.1-8B-Instruct up to 4,096, Mistral Nemo up to 128,000 tokens.

Which can read images, PDFs, audio or video?

GPT-4o mini accepts text, images and PDFs; Llama-3.1-8B-Instruct accepts text; Mistral Nemo accepts text. GPT-4o mini handles the widest range of inputs.

Are any of these open source?

Llama-3.1-8B-Instruct and Mistral Nemo publishes its weights and can be self-hosted; GPT-4o mini is proprietary.

Which is newer?

Llama-3.1-8B-Instruct is the newest, released Jul 23, 2024. GPT-4o mini came out Jul 18, 2024; Mistral Nemo came out Jul 1, 2024. Knowledge cutoff: GPT-4o mini Sep 2023, Llama-3.1-8B-Instruct Dec 2023, Mistral Nemo Jul 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 Oct 4, 2026.

05 — Keep comparing

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