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Llama 4 Maverick vs MiniMax M3

Updated October 14, 2026. Rank says MiniMax M3 is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

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Decision reading

The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. Use the documented cost, context, and runtime rows instead. 0 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A
Meta logo
Llama 4 Maverick

Meta

21.67/100

Supported · Public rank #204

90% interval 17.0–26.3

Model B
MiniMax logo
MiniMax M3

MiniMax

55/100

Supported · Public rank #68

90% interval 45.6–64.4

Shared results
0
Llama 4 Maverick only
0
MiniMax M3 only
27
Like-for-like categories
0 / 8
Supported: Llama 4 Maverick and MiniMax M3How the comparison works

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.

No workload recommendation clears the current evidence threshold.

Use the matched evidence, workload costs, and sourced specifications below instead of treating a point score as a universal answer.

Show secondary and unsupported calls

  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    Llama 4 Maverick is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.

    Confidence: limited

  • Agentic work

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

    Not enough matched evidence

    Llama 4 Maverick is scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.

    Confidence: limited

  • Long documents

    Prompts that approach the documented context limit

    No clear pick

    The documented context windows are equal.

    Confidence: documented

  • 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

Which one for a specific job

Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.

The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.

13.8Llama 4 Maverick36.5MiniMax M3

Directional only · BenchAlign v5.8

MiniMax M3 has the higher coding point estimate. Conditional score ranges do not establish rank confidence.

Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.

Open the coding leaderboardShortlist models for this job
Same basis rules as the category table below

What is actually comparable

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

4 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.

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.

A shared-evidence shape is not available.

BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign v5.8 lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.

Agentic

Directional only
Llama 4 Maverick
10.8
Estimated · #118/125
MiniMax M3
39.6
Supported · #66/125
Basis
BenchAlign v5.8 lane · 0 vs 9 public rows
Reading
Directional only

Coding

Directional only
Llama 4 Maverick
13.8
Estimated · #136/149
MiniMax M3
36.5
Supported · #73/149
Basis
BenchAlign v5.8 lane · 0 vs 10 public rows
Reading
Directional only

Knowledge

Directional only
Llama 4 Maverick
32.2
Estimated · #142/181
MiniMax M3
49.6
Supported · #80/181
Basis
BenchAlign v5.8 lane · 0 vs 2 public rows
Reading
Directional only

Instruction following

Directional only
Llama 4 Maverick
50.3
#89/144
MiniMax M3
93.8
#5/144
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Directional only

Reasoning

Not comparable
Llama 4 Maverick
60.2
Unranked · 2 rankable rows
MiniMax M3
82.9
#5/29
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Llama 4 Maverick
56.0
Unranked · 1 rankable row
MiniMax M3
61.5
#43/54
Basis
Provisional lane · 0 vs 2 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Llama 4 Maverick
Not ranked
MiniMax M3
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Llama 4 Maverick
Not ranked
MiniMax M3
Not ranked
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.8) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

Supported evidence per lane · bars run 0–100Methodology

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 Maverick
Self-hosted; infrastructure cost varies
Fits in one request
MiniMax M3
$0.0009
Fits in one request

Llama 4 Maverick has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Llama 4 Maverick
Self-hosted; infrastructure cost varies
Fits in one request
MiniMax M3
$0.0186
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

Llama 4 Maverick
Self-hosted; infrastructure cost varies
Fits in one request
Cached-input rate unavailable
MiniMax M3
$0.03
Fits in one request

Llama 4 Maverick has no comparable published API token rate.

Cached input falls back to the list input rate only where a cached rate is unpublished

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 Maverick

1M

MiniMax M3

1M

API model ID

Llama 4 Maverick

Not sourced

MiniMax M3

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 Maverick

No comparable hosted API rate

MiniMax M3

$0.06 per 1M cached input tokens

Documented inputs

Llama 4 Maverick

Not sourced

MiniMax M3

Not sourced

Documented outputs

Llama 4 Maverick

Not sourced

MiniMax M3

Not sourced

Provider availability

Llama 4 Maverick

Not sourced

MiniMax M3

Not sourced

Reasoning profile

Llama 4 Maverick

Non-Reasoning

MiniMax M3

Non-Reasoning

Weight access

Llama 4 Maverick

Open Weight

MiniMax M3

Open Weight

License

Llama 4 Maverick

Open Weight

MiniMax M3

Open Weight

Release date

Llama 4 Maverick

2025-04-05

MiniMax M3

2026-06-01

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
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Both models list 1M.
Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Llama 4 Maverick or MiniMax M3?

The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Llama 4 Maverick or MiniMax M3?

MiniMax M3 scores higher for coding on the public lane, 36.5 to 13.8. Llama 4 Maverick is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like. BenchLM does not name a winner for coding from a directional reading; read the shared benchmark rows directly and test the models on the same task set.

Which is better for agentic tasks, Llama 4 Maverick or MiniMax M3?

MiniMax M3 scores higher for agentic tasks on the public lane, 39.6 to 10.8. Llama 4 Maverick is scored on Estimated evidence for agentic tasks, so the reading is directional rather than like-for-like. BenchLM does not name a winner for agentic tasks from a directional reading; read the shared benchmark rows directly and test the models on the same task set.

Which costs less, Llama 4 Maverick or MiniMax M3?

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 Maverick or MiniMax M3?

Both models list the same context window, 1M.

Self-host vs API cost

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

Llama 4 Maverick
API / mo$0
Self-host / mo$2,610
Break-even—
MiniMax M3
API / mo$1,125
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 evidence27 rows

Agentic

  • Terminal-Bench 2.1

    Llama 4 Maverick—
    MiniMax M366.0%
    Source

    Not directly comparable

  • BrowseComp

    Llama 4 Maverick—
    MiniMax M383.5%
    Source

    Not directly comparable

  • OSWorld-Verified

    Llama 4 Maverick—
    MiniMax M370.1%
    Source

    Not directly comparable

  • MCP Atlas

    Llama 4 Maverick—
    MiniMax M374.2%
    Source

    Not directly comparable

  • Claw-Eval

    Llama 4 Maverick—
    MiniMax M374.5%
    Source

    Not directly comparable

  • BankerToolBench

    Llama 4 Maverick—
    MiniMax M376.1%
    Source

    Not directly comparable

  • ResearchClawBench

    Llama 4 Maverick—
    MiniMax M319.8%
    Source

    Not directly comparable

  • OSWorld 2.0

    Llama 4 Maverick—
    MiniMax M34.6%
    Source

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Llama 4 Maverick—
    MiniMax M353.6%
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    Llama 4 Maverick—
    MiniMax M380.5%
    Source

    Not directly comparable

  • SWE-bench Pro

    Llama 4 Maverick—
    MiniMax M359%
    Source

    Not directly comparable

  • Terminal-Bench 2.1

    Llama 4 Maverick—
    MiniMax M366.0%
    Source

    Not directly comparable

  • NL2Repo

    Llama 4 Maverick—
    MiniMax M342.1%
    Source

    Not directly comparable

  • VIBE V2

    Llama 4 Maverick—
    MiniMax M350.1%
    Source

    Not directly comparable

  • SVG-Bench

    Llama 4 Maverick—
    MiniMax M363.7%
    Source

    Not directly comparable

  • KernelBench Hard

    Llama 4 Maverick—
    MiniMax M328.8%
    Source

    Not directly comparable

  • OpenHarmony Bench

    Llama 4 Maverick—
    MiniMax M348.4%
    Source

    Not directly comparable

  • LiveCodeBench (Vals)

    Llama 4 Maverick—
    MiniMax M382.2%
    Source

    Not directly comparable

  • SWE-bench (Vals)

    Llama 4 Maverick—
    MiniMax M375.0%
    Source

    Not directly comparable

Multimodal

  • OfficeQA Pro

    Llama 4 Maverick—
    MiniMax M345.1%
    Source

    Not directly comparable

  • OmniDocBench 1.5

    Llama 4 Maverick—
    MiniMax M391.6%
    Source

    Not directly comparable

  • MMMU-Pro

    Llama 4 Maverick—
    MiniMax M378.1%
    Source

    Not directly comparable

  • VideoMMMU

    Llama 4 Maverick—
    MiniMax M384.6%
    Source

    Not directly comparable

  • Video-MME (with subtitle)

    Llama 4 Maverick—
    MiniMax M385.4%
    Source

    Not directly comparable

Knowledge

  • GPQA Diamond (Vals)

    Llama 4 Maverick—
    MiniMax M392.7%
    Source

    Not directly comparable

  • MMLU-Pro (Vals)

    Llama 4 Maverick—
    MiniMax M384.2%
    Source

    Not directly comparable

Math

  • USAMO 2026

    Llama 4 Maverick—
    MiniMax M385.7%
    Source

    Not directly comparable

27 public results · 0 shared

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Last updated October 14, 2026