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Model A
MiniMax M3

MiniMax

68.5/100

Supported · Public rank #19

90% interval 63.5–73.5

MiniMax M3 vs Ornith-1.0-397B

Updated August 13, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Model B
Ornith-1.0-397B

DeepReinforce AI

Evidence status unavailable

90% interval unavailable

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.

6 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.

  • Coding work

    Code generation, repair, and software-engineering tasks

    Ornith-1.0-397B

    Ornith-1.0-397B leads on the same 2 weighted benchmark rows.

    Confidence: limited

  • Long documents

    Prompts that approach the documented context limit

    MiniMax M3

    MiniMax M3 has the larger documented context window.

    Confidence: documented

Show secondary and unsupported calls
  • Agentic work

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

    Not enough matched evidence

    The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.

    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
6
MiniMax M3 only
16
Ornith-1.0-397B only
1
Like-for-like categories
1 / 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.

Coding

Like-for-like
MiniMax M3
72.2
Ornith-1.0-397B
74.6
Weighted basis
2 vs 2 rows
Reading
Ornith-1.0-397B leads

Agentic

Directional only
MiniMax M3
72.3
Ornith-1.0-397B
77.5
Weighted basis
3 vs 1 rows
Reading
Directional only

Reasoning

Not comparable
MiniMax M3
Not measured
Ornith-1.0-397B
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Knowledge

Not comparable
MiniMax M3
Not measured
Ornith-1.0-397B
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Math

Not comparable
MiniMax M3
85.7
Ornith-1.0-397B
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
MiniMax M3
Not measured
Ornith-1.0-397B
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
MiniMax M3
64.9
Ornith-1.0-397B
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
MiniMax M3
Not measured
Ornith-1.0-397B
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

MiniMax M3
$0.0009
Fits in one request
Ornith-1.0-397B
Self-hosted; infrastructure cost varies
Fits in one request

Ornith-1.0-397B has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

MiniMax M3
$0.0186
Fits in one request
Ornith-1.0-397B
Self-hosted; infrastructure cost varies
Fits in one request

Ornith-1.0-397B has no comparable published API token rate.

Cache-heavy agent loop

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

MiniMax M3
$0.03
Fits in one request
Ornith-1.0-397B
Self-hosted; infrastructure cost varies
Fits in one request
Cached-input rate unavailable

Ornith-1.0-397B 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.

MiniMax M3

1M

Ornith-1.0-397B

256K

API model ID

MiniMax M3

Not sourced

Ornith-1.0-397B

Not sourced

Cached-input rate

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

MiniMax M3

$0.06 per 1M cached input tokens

Ornith-1.0-397B

No comparable hosted API rate

Documented inputs

MiniMax M3

Not sourced

Ornith-1.0-397B

Not sourced

Documented outputs

MiniMax M3

Not sourced

Ornith-1.0-397B

Not sourced

Provider availability

MiniMax M3

Not sourced

Ornith-1.0-397B

Not sourced

Reasoning profile

MiniMax M3

Non-Reasoning

Ornith-1.0-397B

Reasoning

Weight access

MiniMax M3

Open Weight

Ornith-1.0-397B

Open Weight

License

MiniMax M3

Open Weight

Ornith-1.0-397B

Open Weight

Release date

MiniMax M3

2026-06-01

Ornith-1.0-397B

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
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
MiniMax M3 has the larger documented window (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 evidence23 rows

Agentic

  • Terminal-Bench 2.0

    MiniMax M366%
    Source
    Ornith-1.0-397B77.5%
    Source

    Ornith-1.0-397B leads this result

  • BrowseComp

    MiniMax M383.5%
    Source
    Ornith-1.0-397B

    Not directly comparable

  • OSWorld-Verified

    MiniMax M370.1%
    Source
    Ornith-1.0-397B

    Not directly comparable

  • MCP Atlas

    MiniMax M374.2%
    Source
    Ornith-1.0-397B

    Not directly comparable

  • Claw-Eval

    MiniMax M374.5%
    Source
    Ornith-1.0-397B77.1%
    Source

    Ornith-1.0-397B leads this result

  • BankerToolBench

    MiniMax M376.1%
    Source
    Ornith-1.0-397B

    Not directly comparable

  • ResearchClawBench

    MiniMax M319.8%
    Source
    Ornith-1.0-397B

    Not directly comparable

  • OSWorld 2.0

    MiniMax M34.6%
    Source
    Ornith-1.0-397B

    Not directly comparable

Coding

  • SWE-bench Verified

    MiniMax M380.5%
    Source
    Ornith-1.0-397B82.4%
    Source

    Ornith-1.0-397B leads this result

  • SWE-bench Pro

    MiniMax M359%
    Source
    Ornith-1.0-397B62.2%
    Source

    Ornith-1.0-397B leads this result

  • Terminal-Bench 2.0

    MiniMax M366.0%
    Source
    Ornith-1.0-397B77.5%
    Source

    Ornith-1.0-397B leads this result

  • NL2Repo

    MiniMax M342.1%
    Source
    Ornith-1.0-397B48.2%
    Source

    Ornith-1.0-397B leads this result

  • VIBE V2

    MiniMax M350.1%
    Source
    Ornith-1.0-397B

    Not directly comparable

  • SVG-Bench

    MiniMax M363.7%
    Source
    Ornith-1.0-397B

    Not directly comparable

  • KernelBench Hard

    MiniMax M328.8%
    Source
    Ornith-1.0-397B

    Not directly comparable

  • EEBench

    MiniMax M39.2%
    Source
    Ornith-1.0-397B

    Not directly comparable

  • SWE Multilingual

    MiniMax M3
    Ornith-1.0-397B78.9%
    Source

    Not directly comparable

Math

  • USAMO 2026

    MiniMax M385.7%
    Source
    Ornith-1.0-397B

    Not directly comparable

Multimodal

  • OfficeQA Pro

    MiniMax M345.1%
    Source
    Ornith-1.0-397B

    Not directly comparable

  • OmniDocBench 1.5

    MiniMax M391.6%
    Source
    Ornith-1.0-397B

    Not directly comparable

  • MMMU-Pro

    MiniMax M378.1%
    Source
    Ornith-1.0-397B

    Not directly comparable

  • VideoMMMU

    MiniMax M384.6%
    Source
    Ornith-1.0-397B

    Not directly comparable

  • Video-MME (with subtitle)

    MiniMax M385.4%
    Source
    Ornith-1.0-397B

    Not directly comparable

Frequently asked questions

Which is better, MiniMax M3 or Ornith-1.0-397B?

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, MiniMax M3 or Ornith-1.0-397B?

Ornith-1.0-397B leads the like-for-like coding comparison across 2 shared weighted benchmark rows.

Which is better for agentic tasks, MiniMax M3 or Ornith-1.0-397B?

The current agentic tasks averages use different weighted benchmark sets, so BenchLM does not name a winner from them. Read the shared benchmark rows directly and test the models on the same task set.

Which costs less, MiniMax M3 or Ornith-1.0-397B?

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, MiniMax M3 or Ornith-1.0-397B?

MiniMax M3 has the larger documented context window: 1M, compared with 256K.

Related comparisons

Last updated August 13, 2026

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