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BenchLM
Interfaze logo
Model A
Interfaze Beta

Interfaze

—

Evidence status unavailable

90% interval unavailable

Interfaze Beta vs MiniMax M3

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

MiniMax logo
Model B
MiniMax M3

MiniMax

68.73/100

Supported · Public rank #21

90% interval 63.5–74.0

Decision reading

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality 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.

  • Chat turn cost

    1K fresh input + 500 output tokens

    MiniMax M3

    MiniMax M3 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

  • Cache-heavy agent loop cost

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

    MiniMax M3

    MiniMax M3 has the lower estimated token cost for this stated workload. Interfaze Beta has no published cached-input rate, so cached tokens use its listed input rate.

    Confidence: rate-fallback

Show secondary and unsupported calls

  • Repository review cost

    50K fresh input + 3K output tokens

    MiniMax M3

    MiniMax M3 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

  • 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

  • Long documents

    Prompts that approach the documented context limit

    No clear pick

    The documented context windows are equal.

    Confidence: documented

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
Interfaze Beta only
8
MiniMax M3 only
21
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.

Multimodal

Directional only
Interfaze Beta
71.1
MiniMax M3
64.9
Weighted basis
1 vs 2 rows
Reading
Directional only

Agentic

Not comparable
Interfaze Beta
Not measured
MiniMax M3
72.3
Weighted basis
0 vs 3 rows
Reading
Not comparable

Coding

Not comparable
Interfaze Beta
Not measured
MiniMax M3
72.2
Weighted basis
0 vs 2 rows
Reading
Not comparable

Reasoning

Not comparable
Interfaze Beta
Not measured
MiniMax M3
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Knowledge

Not comparable
Interfaze Beta
89.9
MiniMax M3
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Math

Not comparable
Interfaze Beta
Not measured
MiniMax M3
85.7
Weighted basis
0 vs 1 rows
Reading
Not comparable

Multilingual

Not comparable
Interfaze Beta
Not measured
MiniMax M3
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Interfaze Beta
Not measured
MiniMax M3
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.

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

Interfaze Beta
$0.00325
Fits in one request
MiniMax M3
$0.0009
Fits in one request

MiniMax M3 has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Interfaze Beta
$0.0855
Fits in one request
MiniMax M3
$0.0186
Fits in one request

MiniMax M3 has the lower modeled cost

Costs use the listed standard API rates.

Cache-heavy agent loop

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

Interfaze Beta
$0.365
Fits in one request
Cached input priced at the published list-input rate
MiniMax M3
$0.03
Fits in one request

MiniMax M3 has the lower modeled cost

Interfaze Beta has no published cached-input rate, so cached tokens use its listed input 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.

Interfaze Beta

1M

MiniMax M3

1M

API model ID

Interfaze Beta

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.

Interfaze Beta

Not published

MiniMax M3

$0.06 per 1M cached input tokens

Documented inputs

Interfaze Beta

Not sourced

MiniMax M3

Not sourced

Documented outputs

Interfaze Beta

Not sourced

MiniMax M3

Not sourced

Provider availability

Interfaze Beta

Not sourced

MiniMax M3

Not sourced

Reasoning profile

Interfaze Beta

Reasoning

MiniMax M3

Non-Reasoning

Weight access

Interfaze Beta

Proprietary

MiniMax M3

Open Weight

License

Interfaze Beta

Proprietary

MiniMax M3

Open Weight

Release date

Interfaze Beta

2026-05-11

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
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
Workload cost
Repository review: $0.0855 vs $0.0186. Cache-heavy agent loop: $0.365 vs $0.03.
Context tradeoff
Both models list 1M.

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

Benchmark evidence

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

Browse raw public benchmark evidence30 rows

Agentic

  • Terminal-Bench 2.0

    Interfaze Beta—
    MiniMax M366%
    Source

    Not directly comparable

  • BrowseComp

    Interfaze Beta—
    MiniMax M383.5%
    Source

    Not directly comparable

  • OSWorld-Verified

    Interfaze Beta—
    MiniMax M370.1%
    Source

    Not directly comparable

  • MCP Atlas

    Interfaze Beta—
    MiniMax M374.2%
    Source

    Not directly comparable

  • Claw-Eval

    Interfaze Beta—
    MiniMax M374.5%
    Source

    Not directly comparable

  • BankerToolBench

    Interfaze Beta—
    MiniMax M376.1%
    Source

    Not directly comparable

  • ResearchClawBench

    Interfaze Beta—
    MiniMax M319.8%
    Source

    Not directly comparable

  • OSWorld 2.0

    Interfaze Beta—
    MiniMax M34.6%
    Source

    Not directly comparable

Coding

  • Spider 2.0-Lite

    Interfaze Beta52.9%
    Source
    MiniMax M3—

    Not directly comparable

  • SWE-bench Verified

    Interfaze Beta—
    MiniMax M380.5%
    Source

    Not directly comparable

  • SWE-bench Pro

    Interfaze Beta—
    MiniMax M359%
    Source

    Not directly comparable

  • Terminal-Bench 2.0

    Interfaze Beta—
    MiniMax M366.0%
    Source

    Not directly comparable

  • NL2Repo

    Interfaze Beta—
    MiniMax M342.1%
    Source

    Not directly comparable

  • VIBE V2

    Interfaze Beta—
    MiniMax M350.1%
    Source

    Not directly comparable

  • SVG-Bench

    Interfaze Beta—
    MiniMax M363.7%
    Source

    Not directly comparable

  • KernelBench Hard

    Interfaze Beta—
    MiniMax M328.8%
    Source

    Not directly comparable

  • OpenHarmony Bench

    Interfaze Beta—
    MiniMax M348.4%
    Source

    Not directly comparable

Knowledge

  • GPQA

    Interfaze Beta89.9%
    Source
    MiniMax M3—

    Not directly comparable

  • GPQA-D

    Interfaze Beta89.9%
    Source
    MiniMax M3—

    Not directly comparable

  • MMMLU

    Interfaze Beta90.9%
    Source
    MiniMax M3—

    Not directly comparable

Math

  • USAMO 2026

    Interfaze Beta—
    MiniMax M385.7%
    Source

    Not directly comparable

Multimodal

  • OCRBench V2

    Interfaze Beta70.7%
    Source
    MiniMax M3—

    Not directly comparable

  • olmOCR

    Interfaze Beta85.7%
    Source
    MiniMax M3—

    Not directly comparable

  • RefCOCO (avg)

    Interfaze Beta82.1%
    Source
    MiniMax M3—

    Not directly comparable

  • MMMU-Pro

    Interfaze Beta71.1%
    Source
    MiniMax M378.1%
    Source

    MiniMax M3 leads this result

  • OfficeQA Pro

    Interfaze Beta—
    MiniMax M345.1%
    Source

    Not directly comparable

  • OmniDocBench 1.5

    Interfaze Beta—
    MiniMax M391.6%
    Source

    Not directly comparable

  • VideoMMMU

    Interfaze Beta—
    MiniMax M384.6%
    Source

    Not directly comparable

  • Video-MME (with subtitle)

    Interfaze Beta—
    MiniMax M385.4%
    Source

    Not directly comparable

Instruction following

  • SOB Value Acc

    Interfaze Beta79.5%
    Source
    MiniMax M3—

    Not directly comparable

Frequently asked questions

Which is better, Interfaze Beta or MiniMax M3?

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Interfaze Beta or MiniMax M3?

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, Interfaze Beta or MiniMax M3?

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, Interfaze Beta or MiniMax M3?

For the stated presets, chat costs $0.00325 on Interfaze Beta and $0.0009 on MiniMax M3; repository review costs $0.0855 and $0.0186; the cache-heavy agent loop costs $0.365 and $0.03. Interfaze Beta has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, Interfaze Beta or MiniMax M3?

Both models list the same context window, 1M.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated August 30, 2026

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