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Model comparison

Llama 4 Scout vs Gemini 2.0 Flash

MetaLlama 4 Scout
Input
$0.18
Output
$0.59
Context
10M
Released
2025-04-05
Full model page →GoogleGemini 2.0 Flash
Input
$0.10 / 1M tokens (text, image, or video); $0.70 / 1M tokens for audio
Output
$0.40 / 1M tokens
Context
1,048,576 tokens (1M)
Released
2025-02-05
Full model page →
Short answer

Gemini 2.0 Flash scores higher on 2 of the 3 benchmarks both models report (the other leads on 1); Gemini 2.0 Flash is cheaper on input tokens ($0.1 vs $0.2 per 1M, 1.8×); Llama 4 Scout has the larger context window (10M vs 1.048576M); Llama 4 Scout ships open weights while Gemini 2.0 Flash is API-only.

Specs and pricing side by side

SpecLlama 4 ScoutGemini 2.0 Flash
MakerMetaGoogle
Released2025-04-052025-02-05
Context window10M1,048,576 tokens (1M)
Max outputnot published8,192 tokens
Input price$0.18$0.10 / 1M tokens (text, image, or video); $0.70 / 1M tokens for audio
Output price$0.59$0.40 / 1M tokens
Parameters109B total · 17B active (16 experts)Undisclosed — Google never published the parameter count
LicenseLlama 4 Community License AgreementProprietary (Google) — closed source, served only via API
WeightsOpen weightsAPI only
ModalitiesText, Visiontext input, image input, audio input, video input, text output
Knowledge cutoff2024-08August 2024

Benchmarks both models report

BenchmarkLlama 4 ScoutGemini 2.0 Flash
MMLU Pro74.3%76.4%
GPQA Diamond57.2%62.1%
MMMU73.4%70.7%

Scores are as published by each maker or its cited source; harness, reasoning effort and date can differ between rows, so treat small gaps as ties. Sources are listed on each model page.

Which one should you pick?

Pick Llama 4 Scout if…

  • You care about MMMU (it scores higher on 1 shared benchmark).
  • You need the longer context (10M vs 1.048576M).
  • You want to self-host or fine-tune (open weights, Llama 4 Community License Agreement).
  • You need Text / Vision input, which Gemini 2.0 Flash lacks.
  • Your use case is: long-document and large-codebase analysis at up to 10M-token context.

Pick Gemini 2.0 Flash if…

  • You care about MMLU Pro, GPQA Diamond (it scores higher on 2 shared benchmarks).
  • Cost matters: input tokens cost 1.8× less ($0.1 vs $0.2 per 1M).
  • You need text input / image input / audio input / video input / text output input, which Llama 4 Scout lacks.
  • Your use case is: high-volume, cost-sensitive text generation, summarization, and classification.

FAQ

Which is better, Llama 4 Scout or Gemini 2.0 Flash?

Gemini 2.0 Flash scores higher on 2 of the 3 benchmarks both models report (the other leads on 1); Gemini 2.0 Flash is cheaper on input tokens ($0.1 vs $0.2 per 1M, 1.8×); Llama 4 Scout has the larger context window (10M vs 1.048576M); Llama 4 Scout ships open weights while Gemini 2.0 Flash is API-only. The better pick depends on whether you value benchmark scores, price per token, context length or openness for your workload.

How much cheaper is Gemini 2.0 Flash?

Llama 4 Scout: $0.18 input, $0.59 output. Gemini 2.0 Flash: $0.10 / 1M tokens (text, image, or video); $0.70 / 1M tokens for audio input, $0.40 / 1M tokens output (list API prices as published by each maker).

What are the context windows of Llama 4 Scout and Gemini 2.0 Flash?

Llama 4 Scout offers 10M; Gemini 2.0 Flash offers 1,048,576 tokens (1M) with up to 8,192 tokens output.

Is Llama 4 Scout newer than Gemini 2.0 Flash?

Llama 4 Scout was released 2025-04-05; Gemini 2.0 Flash was released 2025-02-05.

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