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MiniMax M3.1 Flash vs Pokee-Isaac 28B

Updated October 19, 2026. We do not rank this pair: at least one has no public score. 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
MiniMax logo

MiniMax

67.05/100

Estimated · Public rank #28

Conditional range 52.7–81.4

Model B
Pokee AI logo

Pokee AI

—

Evidence status unavailable

90% interval unavailable

Shared results
0
MiniMax M3.1 Flash only
12
Pokee-Isaac 28B only
7
Like-for-like categories
0 / 8
Estimated: MiniMax M3.1 Flash. Conditional ranges do not establish rank confidence.How 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.

  • Long documents

    Prompts that approach the documented context limit

    Pokee-Isaac 28B

    Pokee-Isaac 28B has the larger documented context window.

    Confidence: documented
  • Chat turn cost

    1K fresh input + 500 output tokens

    MiniMax M3.1 Flash

    MiniMax M3.1 Flash 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 M3.1 Flash

    MiniMax M3.1 Flash has the lower estimated token cost for this stated workload. Pokee-Isaac 28B 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 M3.1 Flash

    MiniMax M3.1 Flash 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

    Pokee-Isaac 28B is not ranked on the public lane for coding, so no winner is named for coding.

    Confidence: limited
  • Agentic work

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

    Not enough matched evidence

    Pokee-Isaac 28B is not ranked on the public lane for agentic, so no winner is named for agentic.

    Confidence: limited

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.

61.3MiniMax M3.1 Flash—Pokee-Isaac 28B

Not comparable · BenchAlign v5.8

The coding row is not comparable on the public lane: at least one model is not measured or not ranked there.

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

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.

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

Not comparable
MiniMax M3.1 Flash
63.9
Estimated · #19/130
Pokee-Isaac 28B
Not ranked
Basis
BenchAlign v5.8 lane · 6 vs 5 public rows
Reading
Not comparable

Coding

Not comparable
MiniMax M3.1 Flash
61.3
Supported · #17/151
Pokee-Isaac 28B
Not ranked
Basis
BenchAlign v5.8 lane · 3 vs 1 public rows
Reading
Not comparable

Reasoning

Not comparable
MiniMax M3.1 Flash
80.6
Unranked · 2 rankable rows
Pokee-Isaac 28B
57.9
Unranked · 1 rankable row
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Multimodal

Not comparable
MiniMax M3.1 Flash
73.5
#30/55
Pokee-Isaac 28B
Not ranked
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Knowledge

Not comparable
MiniMax M3.1 Flash
73.2
Supported · #14/186
Pokee-Isaac 28B
Not ranked
Basis
BenchAlign v5.8 lane · 1 vs 0 public rows
Reading
Not comparable

Multilingual

Not comparable
MiniMax M3.1 Flash
Not ranked
Pokee-Isaac 28B
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
MiniMax M3.1 Flash
Not ranked
Pokee-Isaac 28B
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
MiniMax M3.1 Flash
Not ranked
Pokee-Isaac 28B
Not ranked
Basis
Provisional lane · 0 vs 0 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

MiniMax M3.1 Flash
$0.00045
Fits in one request
Pokee-Isaac 28B
$0.00065
Fits in one request

MiniMax M3.1 Flash has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

MiniMax M3.1 Flash
$0.0093
Fits in one request
Pokee-Isaac 28B
$0.0105
Fits in one request

MiniMax M3.1 Flash has the lower modeled cost

Costs use the listed standard API rates.

Cache-heavy agent loop

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

MiniMax M3.1 Flash
$0.012
Fits in one request
Pokee-Isaac 28B
$0.043
Fits in one request
Cached input priced at the published list-input rate

MiniMax M3.1 Flash has the lower modeled cost

Pokee-Isaac 28B has no published cached-input rate, so cached tokens use its listed input 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.

Documented inputs

MiniMax M3.1 Flash

Not sourced

Pokee-Isaac 28B

Not sourced

Documented outputs

MiniMax M3.1 Flash

Not sourced

Pokee-Isaac 28B

Not sourced

Provider availability

MiniMax M3.1 Flash

Not sourced

Pokee-Isaac 28B

Not sourced

Reasoning profile

MiniMax M3.1 Flash

Reasoning

Pokee-Isaac 28B

Reasoning

Weight access

MiniMax M3.1 Flash

Proprietary

Pokee-Isaac 28B

Proprietary

License

MiniMax M3.1 Flash

Proprietary

Pokee-Isaac 28B

Proprietary

Release date

MiniMax M3.1 Flash

2026-10-19

Pokee-Isaac 28B

2026-08-03

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
Repository review: $0.0093 vs $0.0105. Cache-heavy agent loop: $0.012 vs $0.043.
Context tradeoff
Pokee-Isaac 28B has the larger documented window (10M).
Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, MiniMax M3.1 Flash or Pokee-Isaac 28B?

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, MiniMax M3.1 Flash or Pokee-Isaac 28B?

Pokee-Isaac 28B is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, MiniMax M3.1 Flash or Pokee-Isaac 28B?

Pokee-Isaac 28B is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, MiniMax M3.1 Flash or Pokee-Isaac 28B?

For the stated presets, chat costs $0.00045 on MiniMax M3.1 Flash and $0.00065 on Pokee-Isaac 28B; repository review costs $0.0093 and $0.0105; the cache-heavy agent loop costs $0.012 and $0.043. Pokee-Isaac 28B has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, MiniMax M3.1 Flash or Pokee-Isaac 28B?

Pokee-Isaac 28B has the larger documented context window: 10M, compared with 1M.

Benchmark evidence

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

Browse raw public benchmark evidence19 rows

Agentic

  • AutomationBench

    MiniMax M3.1 Flash62.2%
    Source
    Pokee-Isaac 28B—

    Not directly comparable

  • BankerToolBench

    MiniMax M3.1 Flash76.2%
    Source
    Pokee-Isaac 28B—

    Not directly comparable

  • Terminal-Bench 4.0

    MiniMax M3.1 Flash38.10%
    Source
    Pokee-Isaac 28B—

    Not directly comparable

  • Agents' Last Exam

    MiniMax M3.1 Flash29.6%
    Source
    Pokee-Isaac 28B—

    Not directly comparable

  • OSWorld 2.0

    MiniMax M3.1 Flash61.7%
    Source
    Pokee-Isaac 28B—

    Not directly comparable

  • CyberGym

    MiniMax M3.1 Flash82.2%
    Source
    Pokee-Isaac 28B—

    Not directly comparable

  • Terminal-Bench 2.1

    MiniMax M3.1 Flash—
    Pokee-Isaac 28B65.1%
    Source

    Not directly comparable

  • BFCL v4

    MiniMax M3.1 Flash—
    Pokee-Isaac 28B70.9%
    Source

    Not directly comparable

  • τ³-bench results

    MiniMax M3.1 Flash—
    Pokee-Isaac 28B66.2%
    Source

    Not directly comparable

  • MCP-Atlas claim coverage

    MiniMax M3.1 Flash—
    Pokee-Isaac 28B74.6%
    Source

    Not directly comparable

  • PinchBench

    MiniMax M3.1 Flash—
    Pokee-Isaac 28B95.7%
    Source

    Not directly comparable

Coding

  • PostTrainBench v1.1

    MiniMax M3.1 Flash39.3%
    Source
    Pokee-Isaac 28B—

    Not directly comparable

  • DeepSWE

    MiniMax M3.1 Flash73.7%
    Source
    Pokee-Isaac 28B—

    Not directly comparable

  • NL2Repo

    MiniMax M3.1 Flash61.2%
    Source
    Pokee-Isaac 28B—

    Not directly comparable

  • Terminal-Bench 2.1

    MiniMax M3.1 Flash—
    Pokee-Isaac 28B65.1%
    Source

    Not directly comparable

Reasoning

  • MRCRv2

    MiniMax M3.1 Flash—
    Pokee-Isaac 28B60.7%
    Source

    Not directly comparable

Multimodal

  • BabyVision w/ Python

    MiniMax M3.1 Flash91.0%
    Source
    Pokee-Isaac 28B—

    Not directly comparable

  • CharXiv

    MiniMax M3.1 Flash82.5%
    Source
    Pokee-Isaac 28B—

    Not directly comparable

Knowledge

  • HLE w/o tools

    MiniMax M3.1 Flash43.4%
    Source
    Pokee-Isaac 28B—

    Not directly comparable

19 public results · 0 shared

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Last updated October 19, 2026