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Thinking Machines Lab logo
Model A
Inkling

Thinking Machines Lab

67.02/100

Supported · Public rank #31

90% interval 60.0–74.0

Inkling vs MiniMax M3

Updated August 29, 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

MiniMax M3 has the higher public score estimate, 68.73 versus 67.02, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

7 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

    MiniMax M3

    MiniMax M3 leads on the same 2 weighted benchmark rows.

    Confidence: limited

  • 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. Costs use the listed standard API rates.

    Confidence: listed-rates

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

  • 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

  • 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
7
Inkling only
8
MiniMax M3 only
15
Like-for-like categories
1 / 8

2 categories use 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
Inkling
68.6
MiniMax M3
72.2
Weighted basis
2 vs 2 rows
Reading
MiniMax M3 leads

Agentic

Directional only
Inkling
69.4
MiniMax M3
72.3
Weighted basis
2 vs 3 rows
Reading
Directional only

Multimodal

Directional only
Inkling
76.5
MiniMax M3
64.9
Weighted basis
2 vs 2 rows
Reading
Directional only

Reasoning

Not comparable
Inkling
Not measured
MiniMax M3
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Knowledge

Not comparable
Inkling
51.6
MiniMax M3
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Math

Not comparable
Inkling
97.1
MiniMax M3
85.7
Weighted basis
1 vs 1 rows
Reading
Not comparable

Multilingual

Not comparable
Inkling
Not measured
MiniMax M3
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Inkling
79.8
MiniMax M3
Not measured
Weighted basis
1 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

Inkling
$0.00421
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

Inkling
$0.10754
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

Inkling
$0.159
Fits in one request
MiniMax M3
$0.03
Fits in one request

MiniMax M3 has the lower modeled cost

Costs use the listed standard API rates.

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.

Inkling

1M

MiniMax M3

1M

API model ID

Inkling

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.

Inkling

$0.374 per 1M cached input tokens

MiniMax M3

$0.06 per 1M cached input tokens

Documented inputs

Inkling

Not sourced

MiniMax M3

Not sourced

Documented outputs

Inkling

Not sourced

MiniMax M3

Not sourced

Provider availability

Inkling

Not sourced

MiniMax M3

Not sourced

Reasoning profile

Inkling

Hybrid

MiniMax M3

Non-Reasoning

Weight access

Inkling

Open Weight

MiniMax M3

Open Weight

License

Inkling

Open Weight

MiniMax M3

Open Weight

Release date

Inkling

2026-07-15

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
MiniMax M3 has the higher public score estimate, 68.73 versus 67.02, but the 90% score intervals overlap.
Workload cost
Repository review: $0.10754 vs $0.0186. Cache-heavy agent loop: $0.159 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

    Inkling63.8%
    Source
    MiniMax M366%
    Source

    MiniMax M3 leads this result

  • BrowseComp

    Inkling77.1%
    Source
    MiniMax M383.5%
    Source

    MiniMax M3 leads this result

  • MCP Atlas

    Inkling74.1%
    Source
    MiniMax M374.2%
    Source

    MiniMax M3 leads this result

  • OSWorld-Verified

    Inkling
    MiniMax M370.1%
    Source

    Not directly comparable

  • Claw-Eval

    Inkling
    MiniMax M374.5%
    Source

    Not directly comparable

  • BankerToolBench

    Inkling
    MiniMax M376.1%
    Source

    Not directly comparable

  • ResearchClawBench

    Inkling
    MiniMax M319.8%
    Source

    Not directly comparable

  • OSWorld 2.0

    Inkling
    MiniMax M34.6%
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    Inkling77.6%
    Source
    MiniMax M380.5%
    Source

    MiniMax M3 leads this result

  • SWE-bench Pro

    Inkling54.3%
    Source
    MiniMax M359%
    Source

    MiniMax M3 leads this result

  • Terminal-Bench 2.0

    Inkling63.8%
    Source
    MiniMax M366.0%
    Source

    MiniMax M3 leads this result

  • NL2Repo

    Inkling
    MiniMax M342.1%
    Source

    Not directly comparable

  • VIBE V2

    Inkling
    MiniMax M350.1%
    Source

    Not directly comparable

  • SVG-Bench

    Inkling
    MiniMax M363.7%
    Source

    Not directly comparable

  • KernelBench Hard

    Inkling
    MiniMax M328.8%
    Source

    Not directly comparable

  • OpenHarmony Bench

    Inkling
    MiniMax M348.4%
    Source

    Not directly comparable

Knowledge

  • GPQA

    Inkling87.9%
    Source
    MiniMax M3

    Not directly comparable

  • GPQA-D

    Inkling87.9%
    Source
    MiniMax M3

    Not directly comparable

  • HLE

    Inkling46%
    Source
    MiniMax M3

    Not directly comparable

  • HLE w/o tools

    Inkling30%
    Source
    MiniMax M3

    Not directly comparable

Math

  • AIME26

    Inkling97.1%
    Source
    MiniMax M3

    Not directly comparable

  • USAMO 2026

    Inkling
    MiniMax M385.7%
    Source

    Not directly comparable

Multimodal

  • MMMU-Pro

    Inkling73.5%
    Source
    MiniMax M378.1%
    Source

    MiniMax M3 leads this result

  • CharXiv

    Inkling82%
    Source
    MiniMax M3

    Not directly comparable

  • CharXiv w/o tools

    Inkling78.1%
    Source
    MiniMax M3

    Not directly comparable

  • OfficeQA Pro

    Inkling
    MiniMax M345.1%
    Source

    Not directly comparable

  • OmniDocBench 1.5

    Inkling
    MiniMax M391.6%
    Source

    Not directly comparable

  • VideoMMMU

    Inkling
    MiniMax M384.6%
    Source

    Not directly comparable

  • Video-MME (with subtitle)

    Inkling
    MiniMax M385.4%
    Source

    Not directly comparable

Instruction following

  • IFBench

    Inkling79.8%
    Source
    MiniMax M3

    Not directly comparable

Frequently asked questions

Which is better, Inkling or MiniMax M3?

MiniMax M3 has the higher public score estimate, 68.73 versus 67.02, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, Inkling or MiniMax M3?

MiniMax M3 leads the like-for-like coding comparison across 2 shared weighted benchmark rows.

Which is better for agentic tasks, Inkling or MiniMax M3?

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, Inkling or MiniMax M3?

For the stated presets, chat costs $0.00421 on Inkling and $0.0009 on MiniMax M3; repository review costs $0.10754 and $0.0186; the cache-heavy agent loop costs $0.159 and $0.03. Costs use the listed standard API rates.

Which has the larger context window, Inkling or MiniMax M3?

Both models list the same context window, 1M.

Related comparisons

Last updated August 29, 2026

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