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Llama 4 Scout vs Parse

Comparing Llama 4 Scout and Parse across benchmarks, pricing, and capabilities.

Meta · Cohere · Updated for 2026

Which is better?

Llama 4 Scout and Parse trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

Llama 4 Scout also accepts a larger context window (10,000,000 input tokens), making it the stronger choice for long documents and large codebases.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Llama 4 Scout

  • you process long inputs — it offers a 10,000,000 token context window
  • you need open weights you can self-host or fine-tune

Choose Parse

  • you want the most recent training data — it shipped Aug 2026

At a glance

The differences that matter most.

Benchmark wins
Input price
$0.08 / M
— / M
Output price
$0.30 / M
— / M
Context window
10,000,000
8,192

Individual benchmarks

12 reported for Llama 4 Scout · 1 for Parse

No common benchmarks found

Llama 4 Scout and Parsedon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

106.7B diff

Llama 4 Scout has 106.7B more parameters than Parse, making it 4639.1% larger.

Meta
Llama 4 Scout
109.0Bparameters
Cohere
Parse
2.3Bparameters
109.0B
Llama 4 Scout
2.3B
Parse

Context Window

Maximum input and output token capacity

Llama 4 Scout accepts 10,000,000 input tokens compared to Parse's 8,192 tokens. Only Llama 4 Scout specifies output context (10,000,000 tokens).

Meta
Llama 4 Scout
Input10,000,000 tokens
Output10,000,000 tokens
Cohere
Parse
Input8,192 tokens
Output- tokens
Mon Aug 31 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Llama 4 Scout and Parse support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Llama 4 Scout

Text
Images
Audio
Video

Parse

Text
Images
Audio
Video

License

Usage and distribution terms

Llama 4 Scout is licensed under Llama 4 Community License Agreement, while Parse uses a proprietary license.

License differences may affect how you can use these models in commercial or open-source projects.

Llama 4 Scout

Llama 4 Community License Agreement

Open weights

Parse

Proprietary

Closed source

Release Timeline

When each model was launched

Llama 4 Scout was released on 2025-04-05, while Parse was released on 2026-08-27.

Parse is 17 months newer than Llama 4 Scout.

Llama 4 Scout

Apr 5, 2025

1.4 years ago

Parse

Aug 27, 2026

4 days ago

1.4yr newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

Llama 4 Scout is available from DeepInfra, Lambda, Novita, Groq, Fireworks, Together. Parse is available from Azure, Cohere.

Llama 4 Scout

deepinfra logo
Deepinfra
Input Price:Input: $0.08/1MOutput Price:Output: $0.30/1M
lambda logo
Lambda
Input Price:Input: $0.08/1MOutput Price:Output: $0.30/1M
novita logo
Novita
Input Price:Input: $0.10/1MOutput Price:Output: $0.50/1M
groq logo
Groq
Input Price:Input: $0.11/1MOutput Price:Output: $0.34/1M
fireworks logo
Fireworks
Input Price:Input: $0.15/1MOutput Price:Output: $0.60/1M
together logo
Together
Input Price:Input: $0.18/1MOutput Price:Output: $0.59/1M

Parse

azure logo
Azure
cohere logo
Cohere
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against Llama 4 Scout and Parse side-by-side, then vote on the output you prefer.

Llama 4 Scout
✓ Preferred
Parse
Open in Playground

FAQ

Common questions about Llama 4 Scout vs Parse.

Which is better, Llama 4 Scout or Parse?

Llama 4 Scout (Meta) and Parse (Cohere) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does Llama 4 Scout compare to Parse in benchmarks?

Llama 4 Scout scores DocVQA: 94.4%, MGSM: 90.6%, ChartQA: 88.8%, MMLU: 79.6%, MMLU-Pro: 74.3%. Parse scores ParseBench: 79.2%.

What are the context window sizes for Llama 4 Scout and Parse?

Llama 4 Scout supports 10.0M tokens and Parse supports 8K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Llama 4 Scout and Parse?

Key differences include context window (10.0M vs 8K), licensing (Llama 4 Community License Agreement vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes Llama 4 Scout and Parse?

Llama 4 Scout is developed by Meta and Parse is developed by Cohere.