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Model comparison

GPT-5.4 mini vs Llama 4 Maverick

Updated July 30, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

GPT-5.4 mini

OpenAI

55.8/100

Estimated · Public rank #81

90% interval 44.3–67.3

Llama 4 Maverick

Meta

22.7/100

Supported · Public rank #201

90% interval 14.9–30.4

GPT-5.4 mini has the higher public score, 55.79 versus 22.7, and the 90% score intervals do not overlap.

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 Maverick

    Llama 4 Maverick 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
GPT-5.4 mini only
13
Llama 4 Maverick only
0
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
GPT-5.4 mini
21.7
Llama 4 Maverick
0.7
Weighted basis
2 vs 1 rows
Reading
Directional only

Agentic

Not comparable
GPT-5.4 mini
65.7
Llama 4 Maverick
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Coding

Not comparable
GPT-5.4 mini
Not measured
Llama 4 Maverick
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Reasoning

Not comparable
GPT-5.4 mini
Not measured
Llama 4 Maverick
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Knowledge

Not comparable
GPT-5.4 mini
47.8
Llama 4 Maverick
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
GPT-5.4 mini
Not measured
Llama 4 Maverick
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
GPT-5.4 mini
76.6
Llama 4 Maverick
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
GPT-5.4 mini
Not measured
Llama 4 Maverick
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

    GPT-5.4 mini: 28.280%Llama 4 Maverick: 0.690%Normalized gap 27.6Shared 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

GPT-5.4 mini
$0.003
Fits in one request
Llama 4 Maverick
Self-hosted; infrastructure cost varies
Fits in one request

Llama 4 Maverick has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

GPT-5.4 mini
$0.051
Fits in one request
Llama 4 Maverick
Self-hosted; infrastructure cost varies
Fits in one request

Llama 4 Maverick has no comparable published API token rate.

Cache-heavy agent loop

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

GPT-5.4 mini
$0.075
Fits in one request
Llama 4 Maverick
Self-hosted; infrastructure cost varies
Fits in one request
Cached-input rate unavailable

Llama 4 Maverick 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.

Cached-input rate

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

GPT-5.4 mini

$0.075 per 1M cached input tokens

OpenAI pricing

Llama 4 Maverick

No comparable hosted API rate

Provider availability

GPT-5.4 mini

Generally Available · OpenAI Responses API

OpenAI model catalog

Llama 4 Maverick

Not sourced

Reasoning profile

GPT-5.4 mini

Reasoning

Llama 4 Maverick

Non-Reasoning

Weight access

GPT-5.4 mini

Proprietary

Llama 4 Maverick

Open Weight

License

GPT-5.4 mini

Proprietary

Llama 4 Maverick

Open Weight

Release date

GPT-5.4 mini

2026-03-17

Llama 4 Maverick

2026-02-28

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
GPT-5.4 mini has the higher public score, 55.79 versus 22.7, and the 90% score intervals do not overlap.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Llama 4 Maverick has the larger documented window (1M).

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.

GPT-5.4 mini
API / mo$3,938
Self-host / moNot listed
Break-even
Proprietary model — self-hosting not applicable.
Llama 4 Maverick
API / mo$0
Self-host / mo$2,610
Break-even
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 evidence14 rows

Agentic

  • Terminal-Bench 2.0

    GPT-5.4 mini60%
    Source
    Llama 4 Maverick

    Not directly comparable

  • OSWorld-Verified

    GPT-5.4 mini72.1%
    Source
    Llama 4 Maverick

    Not directly comparable

  • MCP Atlas

    GPT-5.4 mini57.7%
    Source
    Llama 4 Maverick

    Not directly comparable

  • Toolathlon

    GPT-5.4 mini42.9%
    Source
    Llama 4 Maverick

    Not directly comparable

  • τ²-bench results

    GPT-5.4 mini93.4%
    Source
    Llama 4 Maverick

    Not directly comparable

Coding

  • Vibe Code Bench

    GPT-5.4 mini47.97%
    Source
    Llama 4 Maverick

    Not directly comparable

  • FrontierCode 1.1 Main

    GPT-5.4 mini27.0%
    Source
    Llama 4 Maverick

    Not directly comparable

Knowledge

  • GPQA

    GPT-5.4 mini88%
    Source
    Llama 4 Maverick

    Not directly comparable

  • HLE

    GPT-5.4 mini41.5%
    Source
    Llama 4 Maverick

    Not directly comparable

  • HLE w/o tools

    GPT-5.4 mini28.2%
    Source
    Llama 4 Maverick

    Not directly comparable

Math

  • FrontierMath v2 (Tiers 1-3)

    Shared source
    GPT-5.4 mini28.280%
    Llama 4 Maverick0.690%

    GPT-5.4 mini leads this result

  • FrontierMath v2 (Tier 4)

    GPT-5.4 mini2.080%
    Source
    Llama 4 Maverick

    Not directly comparable

Multimodal

  • MMMU-Pro

    GPT-5.4 mini76.6%
    Source
    Llama 4 Maverick

    Not directly comparable

  • MMMU-Pro w/ Python

    GPT-5.4 mini78%
    Source
    Llama 4 Maverick

    Not directly comparable

Frequently asked questions

Which is better, GPT-5.4 mini or Llama 4 Maverick?

GPT-5.4 mini has the higher public score, 55.79 versus 22.7, and the 90% score intervals do not overlap. That is the clearest overall quality signal in the current public data.

Which is better for coding, GPT-5.4 mini or Llama 4 Maverick?

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, GPT-5.4 mini or Llama 4 Maverick?

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, GPT-5.4 mini or Llama 4 Maverick?

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, GPT-5.4 mini or Llama 4 Maverick?

Llama 4 Maverick has the larger documented context window: 1M, compared with 400K.

Related comparisons

Last updated July 30, 2026

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