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Comparison · 2 models · Updated Oct 4, 2026

Llama 4 Scout 17B Instruct vs MiniMax-M2.7

Too close to call on our weighted score (Llama 4 Scout 17B Instruct 62, MiniMax-M2.7 61). The right pick depends on what you value most.

  1. 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

  2. MiniMax

    MiniMax-M2.7

    Released Mar 18, 2026

    61/100
    • ECI145.9
    • Price$0.30 / $1.20
    • Context205K
    Full specs Remove MiniMax-M2.7

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01 — Verdict

Too close to call

It is close. Our weighted score puts them within 1 points (Llama 4 Scout 17B Instruct 62/100, MiniMax-M2.7 61/100), so choose by what matters most for your work: MiniMax-M2.7 for raw capability, Llama 4 Scout 17B Instruct on price and Llama 4 Scout 17B Instruct for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityMiniMax-M2.7Capabilities Index (ECI): MiniMax-M2.7 145.9 · Llama 4 Scout 17B Instruct 129.7
  • Lowest priceLlama 4 Scout 17B InstructLlama 4 Scout 17B Instruct $0.341 · MiniMax-M2.7 $0.525 per 1M tokens (3:1 blend)
  • Longest contextLlama 4 Scout 17B InstructLlama 4 Scout 17B Instruct 10,000,000 · MiniMax-M2.7 204,800 tokens
  • Widest inputsLlama 4 Scout 17B InstructLlama 4 Scout 17B Instruct: Text, Images · MiniMax-M2.7: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightLlama 4 Scout 17B InstructMiniMax-M2.7
CapabilityCapabilities Index (ECI)50%5273
Price25%7263
Inputs & features15%5035
Context window10%10032
Overall100%62/10061/100
02 — Side by side

Every spec in one table

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

Llama 4 Scout 17B Instruct vs MiniMax-M2.7 specifications side by side
SpecificationLlama 4 Scout 17B InstructMetaMiniMax-M2.7MiniMax
Capability
Capabilities Index (ECI)129.7145.9 (best)
ECI rank#126 of 148#73 of 148 (best)
GPQA DiamondGraduate-level science questions51.8%—
OTIS Mock AIME 2024–2025Competition mathematics7.8%—
Price per million tokens
Input$0.225 (best)$0.30
Output$0.69 (best)$1.20
Cached input—$0.06
Blended (3:1)$0.341 (best)$0.525
Long-context rateSame rateSame rate
Price sourceMedian of 4 providersOfficial MiniMax (minimax.io) API
Limits
Context window10,000,000 tokens (best)204,800 tokens
Max output16,384 tokens131,072 tokens (best)
Inputs and features
TextYesYes
ImagesYesNo
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningNoYes
Tool callingYesYes
Structured outputNoNo
Availability
WeightsOpenOpen
API model ID—MiniMax-M2.7
API providers429 (best)
ReleasedApr 5, 2025Mar 18, 2026
Knowledge cutoffAug 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 4 Scout 17B Instruct$3.63
  • MiniMax-M2.7$5.40
04 — Questions

Which should you choose?

Which is better: Llama 4 Scout 17B Instruct or MiniMax-M2.7?

It is close. Our weighted score puts them within 1 points (Llama 4 Scout 17B Instruct 62/100, MiniMax-M2.7 61/100), so choose by what matters most for your work: MiniMax-M2.7 for raw capability, Llama 4 Scout 17B Instruct on price and Llama 4 Scout 17B Instruct for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Llama 4 Scout 17B Instruct or MiniMax-M2.7?

Llama 4 Scout 17B Instruct is cheaper at $0.225 input / $0.69 output per million tokens (median across 4 API providers). MiniMax-M2.7 costs $0.30 input / $1.20 output per million tokens (official MiniMax (minimax.io) API price). At a typical mix of three input tokens to one output token, that is $0.341 per million tokens for Llama 4 Scout 17B Instruct versus $0.525 for MiniMax-M2.7 (1.5× as much).

Which scores higher on benchmarks?

MiniMax-M2.7 scores higher on the Capabilities Index (ECI): MiniMax-M2.7 145.9 (#73 of 148) and Llama 4 Scout 17B Instruct 129.7 (#126 of 148). Their confidence ranges do not overlap (138.2–148.0 vs 124.8–131.4), so the gap is a real one.

Which is better for coding?

There are no published SWE-bench Verified results for Llama 4 Scout 17B Instruct and MiniMax-M2.7 yet, so there is no like-for-like coding score. On overall capability, MiniMax-M2.7 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 204,800 for MiniMax-M2.7. Maximum output per response: Llama 4 Scout 17B Instruct up to 16,384, MiniMax-M2.7 up to 131,072 tokens.

Which can read images, PDFs, audio or video?

Llama 4 Scout 17B Instruct accepts text and images; MiniMax-M2.7 accepts text. Llama 4 Scout 17B Instruct 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?

MiniMax-M2.7 is the newest, released Mar 18, 2026. Llama 4 Scout 17B Instruct came out Apr 5, 2025. Knowledge cutoff: 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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