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Model comparison

Llama 4 Scout vs Qwen 3.6 Max (preview)

Updated August 11, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Llama 4 Scout

Meta

39.3/100

Supported · Public rank #191

90% interval 20.8–57.8

Qwen 3.6 Max (preview)

Alibaba

59.6/100

Supported · Public rank #56

90% interval 40.8–78.5

Qwen 3.6 Max (preview) has the higher public score estimate, 59.65 versus 39.28, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

1 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.

Which one for your work

Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.

  • Long documents

    Prompts that approach the documented context limit

    Llama 4 Scout

    Llama 4 Scout has the larger documented context window.

    Confidence: documented

Show secondary and unsupported calls

  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    No shared weighted benchmark basis supports a winner.

    Confidence: limited

  • Agentic work

    Tool use, computer use, and multi-step task completion

    Not enough matched evidence

    No shared weighted benchmark basis supports a winner.

    Confidence: limited

  • Chat turn cost

    1K fresh input + 500 output tokens

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates

  • Cache-heavy agent loop cost

    200K cached + 20K fresh input + 10K output tokens

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates

  • Repository review cost

    50K fresh input + 3K output tokens

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

Shared results
1
Llama 4 Scout only
0
Qwen 3.6 Max (preview) only
8
Like-for-like categories
0 / 8

1 category uses different evidence sets. Those rows remain visible for coverage context but do not name a winner.

Category results, on a stated basis

Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.

Math

Directional only
Llama 4 Scout
Not measured
Qwen 3.6 Max (preview)
18.4
Weighted basis
1 vs 2 rows
Reading
Directional only

Agentic

Not comparable
Llama 4 Scout
Not measured
Qwen 3.6 Max (preview)
65.4
Weighted basis
0 vs 1 rows
Reading
Not comparable

Coding

Not comparable
Llama 4 Scout
Not measured
Qwen 3.6 Max (preview)
51.0
Weighted basis
0 vs 2 rows
Reading
Not comparable

Reasoning

Not comparable
Llama 4 Scout
Not measured
Qwen 3.6 Max (preview)
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Knowledge

Not comparable
Llama 4 Scout
Not measured
Qwen 3.6 Max (preview)
73.9
Weighted basis
0 vs 1 rows
Reading
Not comparable

Multilingual

Not comparable
Llama 4 Scout
Not measured
Qwen 3.6 Max (preview)
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
Llama 4 Scout
Not measured
Qwen 3.6 Max (preview)
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Llama 4 Scout
Not measured
Qwen 3.6 Max (preview)
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Shape of the matched evidence

Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.

Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.

  • FrontierMath v2 (Tiers 1-3)

    Math

    Llama 4 Scout: 0.000%Qwen 3.6 Max (preview): 23.103%Normalized gap 23.1Shared source

What each workload costs

Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.

Chat turn

1K fresh input + 500 output tokens

Llama 4 Scout
Self-hosted; infrastructure cost varies
Fits in one request
Qwen 3.6 Max (preview)
API rate not published
Fits in one request

Llama 4 Scout has no comparable published API token rate. Qwen 3.6 Max (preview) has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Llama 4 Scout
Self-hosted; infrastructure cost varies
Fits in one request
Qwen 3.6 Max (preview)
API rate not published
Fits in one request

Llama 4 Scout has no comparable published API token rate. Qwen 3.6 Max (preview) has no comparable published API token rate.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

Llama 4 Scout
Self-hosted; infrastructure cost varies
Fits in one request
Cached-input rate unavailable
Qwen 3.6 Max (preview)
API rate not published
Fits in one request
Cached-input rate unavailable

Llama 4 Scout has no comparable published API token rate. Qwen 3.6 Max (preview) has no comparable published API token rate.

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

Context window

Maximum documented context; output-token limits may be lower.

Llama 4 Scout

10M

Qwen 3.6 Max (preview)

256K

API model ID

Llama 4 Scout

Not sourced

Qwen 3.6 Max (preview)

Not sourced

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

Llama 4 Scout

No comparable hosted API rate

Qwen 3.6 Max (preview)

No comparable hosted API rate

Documented inputs

Llama 4 Scout

Not sourced

Qwen 3.6 Max (preview)

Not sourced

Documented outputs

Llama 4 Scout

Not sourced

Qwen 3.6 Max (preview)

Not sourced

Provider availability

Llama 4 Scout

Not sourced

Qwen 3.6 Max (preview)

Not sourced

Reasoning profile

Llama 4 Scout

Non-Reasoning

Qwen 3.6 Max (preview)

Reasoning

Weight access

Llama 4 Scout

Open Weight

Qwen 3.6 Max (preview)

Proprietary

License

Llama 4 Scout

Open Weight

Qwen 3.6 Max (preview)

Proprietary

Release date

Llama 4 Scout

2026-02-28

Qwen 3.6 Max (preview)

2026-04-20

If you already use one of these models
Deployment change
The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
Quality signal
Qwen 3.6 Max (preview) has the higher public score estimate, 59.65 versus 39.28, but the 90% score intervals overlap.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Llama 4 Scout has the larger documented window (10M).

Run the same representative tasks against both endpoints before changing production traffic.

Self-host vs API cost

Estimates at 50,000 req/day · 1000 tokens/req average.

Llama 4 Scout
API / mo$0
Self-host / mo$2,278
Break-even—
Qwen 3.6 Max (preview)
API / mo$0
Self-host / moNot listed
Break-even—
Proprietary model — self-hosting not applicable.
Model the full break-even

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence9 rows

Agentic

  • Terminal-Bench 2.0

    Llama 4 Scout—
    Qwen 3.6 Max (preview)65.4%
    Source

    Not directly comparable

  • QwenClawBench

    Llama 4 Scout—
    Qwen 3.6 Max (preview)59.0%
    Source

    Not directly comparable

Coding

  • SWE-bench Pro

    Llama 4 Scout—
    Qwen 3.6 Max (preview)57.3%
    Source

    Not directly comparable

  • SciCode

    Llama 4 Scout—
    Qwen 3.6 Max (preview)47%
    Source

    Not directly comparable

  • NL2Repo

    Llama 4 Scout—
    Qwen 3.6 Max (preview)42.9%
    Source

    Not directly comparable

  • Terminal-Bench 2.0

    Llama 4 Scout—
    Qwen 3.6 Max (preview)65.4%
    Source

    Not directly comparable

Knowledge

  • SuperGPQA

    Llama 4 Scout—
    Qwen 3.6 Max (preview)73.9%
    Source

    Not directly comparable

Math

  • FrontierMath v2 (Tiers 1-3)

    Shared source
    Llama 4 Scout0.000%
    Qwen 3.6 Max (preview)23.103%

    Qwen 3.6 Max (preview) leads this result

  • FrontierMath v2 (Tier 4)

    Llama 4 Scout—
    Qwen 3.6 Max (preview)4.167%
    Source

    Not directly comparable

Frequently asked questions

Which is better, Llama 4 Scout or Qwen 3.6 Max (preview)?

Qwen 3.6 Max (preview) has the higher public score estimate, 59.65 versus 39.28, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, Llama 4 Scout or Qwen 3.6 Max (preview)?

The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.

Which is better for agentic tasks, Llama 4 Scout or Qwen 3.6 Max (preview)?

The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.

Which costs less, Llama 4 Scout or Qwen 3.6 Max (preview)?

Both models do not have comparable published API token rates, so this page does not name a universal price winner.

Which has the larger context window, Llama 4 Scout or Qwen 3.6 Max (preview)?

Llama 4 Scout has the larger documented context window: 10M, compared with 256K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated August 11, 2026

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