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Comparison · 2 models · Updated Oct 4, 2026

GPT-4.1 nano vs Llama 4 Scout 17B Instruct

Too close to call on our weighted score (GPT-4.1 nano 63, Llama 4 Scout 17B Instruct 62). The right pick depends on what you value most.

  1. OpenAI

    GPT-4.1 nano

    Released Apr 14, 2025Deprecated

    63/100
    • ECI129.6
    • Price$0.10 / $0.40
    • Context1.05M
    Full specs Remove GPT-4.1 nano

  2. Meta

    Llama 4 Scout 17B Instruct

    Released Apr 5, 2025

    62/100
    • ECI129.7
    • Price$0.225 / $0.69
    • Context10M
    Full specs Remove Llama 4 Scout 17B Instruct

  3. Add a model

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01 — Verdict

Too close to call

It is close. Our weighted score puts them within a point (GPT-4.1 nano 63/100, Llama 4 Scout 17B Instruct 62/100), so choose by what matters most for your work: Llama 4 Scout 17B Instruct for raw capability and GPT-4.1 nano on price. 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 · GPT-4.1 nano 129.6
  • Lowest priceGPT-4.1 nanoGPT-4.1 nano $0.175 · 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 · GPT-4.1 nano 1,047,576 tokens
  • Widest inputsSame inputsGPT-4.1 nano: Text, Images · Llama 4 Scout 17B Instruct: Text, Images
  • Self-hostingLlama 4 Scout 17B InstructPublishes downloadable weights
How the score is built
MeasureWeightGPT-4.1 nanoLlama 4 Scout 17B Instruct
CapabilityCapabilities Index (ECI)50%5252
Price25%8672
Inputs & features15%6050
Context window10%61100
Overall100%63/10062/100
02 — Side by side

Every spec in one table

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

GPT-4.1 nano vs Llama 4 Scout 17B Instruct specifications side by side
SpecificationGPT-4.1 nanoOpenAILlama 4 Scout 17B InstructMeta
Capability
Capabilities Index (ECI)129.6129.7 (best)
ECI rank#127 of 148#126 of 148 (best)
GPQA DiamondGraduate-level science questions48.9%51.8% (best)
OTIS Mock AIME 2024–2025Competition mathematics28.9% (best)7.8%
SimpleQA VerifiedShort factual questions6.0%—
Price per million tokens
Input$0.10 (best)$0.225
Output$0.40 (best)$0.69
Cached input$0.025—
Blended (3:1)$0.175 (best)$0.341
Long-context rateSame rateSame rate
Price sourceOfficial OpenAI APIMedian of 4 providers
Limits
Context window1,047,576 tokens10,000,000 tokens (best)
Max output32,768 tokens (best)16,384 tokens
Inputs and features
TextYesYes
ImagesYesYes
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningNoNo
Tool callingYesYes
Structured outputYesNo
Availability
WeightsProprietaryOpen
API model IDgpt-4.1-nano—
API providers20 (best)4
ReleasedApr 14, 2025Apr 5, 2025
Knowledge cutoffApr 2024Aug 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-4.1 nano$1.80
  • Llama 4 Scout 17B Instruct$3.63
04 — Questions

Which should you choose?

Which is better: GPT-4.1 nano or Llama 4 Scout 17B Instruct?

It is close. Our weighted score puts them within a point (GPT-4.1 nano 63/100, Llama 4 Scout 17B Instruct 62/100), so choose by what matters most for your work: Llama 4 Scout 17B Instruct for raw capability and GPT-4.1 nano on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, GPT-4.1 nano or Llama 4 Scout 17B Instruct?

GPT-4.1 nano is cheaper at $0.10 input / $0.40 output per million tokens (official OpenAI API price). 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 $0.175 per million tokens for GPT-4.1 nano versus $0.341 for Llama 4 Scout 17B Instruct (2× 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) and GPT-4.1 nano 129.6 (#127 of 148). The confidence ranges of the top two overlap (124.8–131.4 vs 123.2–132.0), so treat the gap as small. On individual benchmarks: GPQA Diamond — Llama 4 Scout 17B Instruct 51.8%, GPT-4.1 nano 48.9%; OTIS Mock AIME 2024–2025 — GPT-4.1 nano 28.9%, Llama 4 Scout 17B Instruct 7.8%.

Which is better for coding?

There are no published SWE-bench Verified results for GPT-4.1 nano and Llama 4 Scout 17B 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. Both 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 1,047,576 for GPT-4.1 nano. Maximum output per response: GPT-4.1 nano up to 32,768, Llama 4 Scout 17B Instruct up to 16,384 tokens.

Which can read images, PDFs, audio or video?

GPT-4.1 nano accepts text and images; Llama 4 Scout 17B Instruct accepts text and images. They handle the same number of input types.

Are any of these open source?

Llama 4 Scout 17B Instruct publishes its weights and can be self-hosted; GPT-4.1 nano is proprietary.

Which is newer?

GPT-4.1 nano is the newest, released Apr 14, 2025. Llama 4 Scout 17B Instruct came out Apr 5, 2025. Knowledge cutoff: GPT-4.1 nano Apr 2024, Llama 4 Scout 17B Instruct Aug 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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