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BenchLM
Data

HeyGen Voice vs MiniMax M3

Updated October 14, 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
HeyGen Voice

HeyGen

—

Evidence status unavailable

90% interval unavailable

Model B
MiniMax logo
MiniMax M3

MiniMax

55/100

Supported · Public rank #68

90% interval 45.6–64.4

Shared results
0
HeyGen Voice only
0
MiniMax M3 only
27
Like-for-like categories
0 / 8
Supported: 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

    HeyGen Voice 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

    HeyGen Voice is not ranked on the public lane for agentic, so no winner is named for agentic.

    Confidence: limited

  • Long documents

    Prompts that approach the documented context limit

    Not enough matched evidence

    A complete context comparison is not sourced.

    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

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.

—HeyGen Voice36.5MiniMax M3

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.

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.

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
HeyGen Voice
Not ranked
MiniMax M3
39.6
Supported · #66/125
Basis
BenchAlign v5.8 lane · 0 vs 9 public rows
Reading
Not comparable

Coding

Not comparable
HeyGen Voice
Not ranked
MiniMax M3
36.5
Supported · #73/149
Basis
BenchAlign v5.8 lane · 0 vs 10 public rows
Reading
Not comparable

Reasoning

Not comparable
HeyGen Voice
Not ranked
MiniMax M3
82.9
#5/29
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
HeyGen Voice
Not ranked
MiniMax M3
61.5
#43/54
Basis
Provisional lane · 0 vs 2 weighted rows
Reading
Not comparable

Knowledge

Not comparable
HeyGen Voice
Not ranked
MiniMax M3
49.6
Supported · #80/181
Basis
BenchAlign v5.8 lane · 0 vs 2 public rows
Reading
Not comparable

Multilingual

Not comparable
HeyGen Voice
Not ranked
MiniMax M3
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
HeyGen Voice
Not ranked
MiniMax M3
93.8
#5/144
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
HeyGen Voice
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

HeyGen Voice
API rate not published
Fit state unavailable
MiniMax M3
$0.0009
Fits in one request

HeyGen Voice has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

HeyGen Voice
API rate not published
Fit state unavailable
MiniMax M3
$0.0186
Fits in one request

HeyGen Voice has no comparable published API token rate.

Cache-heavy agent loop

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

HeyGen Voice
API rate not published
Fit state unavailable
Cached-input rate unavailable
MiniMax M3
$0.03
Fits in one request

HeyGen Voice 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.

HeyGen Voice

N/A

MiniMax M3

1M

API model ID

HeyGen Voice

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.

HeyGen Voice

No comparable hosted API rate

HeyGen model documentation

MiniMax M3

$0.06 per 1M cached input tokens

Documented inputs

HeyGen Voice

Not sourced

MiniMax M3

Not sourced

Documented outputs

HeyGen Voice

Not sourced

MiniMax M3

Not sourced

Provider availability

HeyGen Voice

Not sourced

MiniMax M3

Not sourced

Reasoning profile

HeyGen Voice

Non-Reasoning

MiniMax M3

Non-Reasoning

Weight access

HeyGen Voice

Proprietary

MiniMax M3

Open Weight

License

HeyGen Voice

Proprietary

MiniMax M3

Open Weight

Release date

HeyGen Voice

Not sourced

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
A complete documented context comparison is not available.
Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, HeyGen Voice 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, HeyGen Voice or MiniMax M3?

HeyGen Voice is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, HeyGen Voice or MiniMax M3?

HeyGen Voice is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, HeyGen Voice 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, HeyGen Voice or MiniMax M3?

A complete documented context-window comparison is not available.

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

    HeyGen Voice—
    MiniMax M366.0%
    Source

    Not directly comparable

  • BrowseComp

    HeyGen Voice—
    MiniMax M383.5%
    Source

    Not directly comparable

  • OSWorld-Verified

    HeyGen Voice—
    MiniMax M370.1%
    Source

    Not directly comparable

  • MCP Atlas

    HeyGen Voice—
    MiniMax M374.2%
    Source

    Not directly comparable

  • Claw-Eval

    HeyGen Voice—
    MiniMax M374.5%
    Source

    Not directly comparable

  • BankerToolBench

    HeyGen Voice—
    MiniMax M376.1%
    Source

    Not directly comparable

  • ResearchClawBench

    HeyGen Voice—
    MiniMax M319.8%
    Source

    Not directly comparable

  • OSWorld 2.0

    HeyGen Voice—
    MiniMax M34.6%
    Source

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    HeyGen Voice—
    MiniMax M353.6%
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    HeyGen Voice—
    MiniMax M380.5%
    Source

    Not directly comparable

  • SWE-bench Pro

    HeyGen Voice—
    MiniMax M359%
    Source

    Not directly comparable

  • Terminal-Bench 2.1

    HeyGen Voice—
    MiniMax M366.0%
    Source

    Not directly comparable

  • NL2Repo

    HeyGen Voice—
    MiniMax M342.1%
    Source

    Not directly comparable

  • VIBE V2

    HeyGen Voice—
    MiniMax M350.1%
    Source

    Not directly comparable

  • SVG-Bench

    HeyGen Voice—
    MiniMax M363.7%
    Source

    Not directly comparable

  • KernelBench Hard

    HeyGen Voice—
    MiniMax M328.8%
    Source

    Not directly comparable

  • OpenHarmony Bench

    HeyGen Voice—
    MiniMax M348.4%
    Source

    Not directly comparable

  • LiveCodeBench (Vals)

    HeyGen Voice—
    MiniMax M382.2%
    Source

    Not directly comparable

  • SWE-bench (Vals)

    HeyGen Voice—
    MiniMax M375.0%
    Source

    Not directly comparable

Multimodal

  • OfficeQA Pro

    HeyGen Voice—
    MiniMax M345.1%
    Source

    Not directly comparable

  • OmniDocBench 1.5

    HeyGen Voice—
    MiniMax M391.6%
    Source

    Not directly comparable

  • MMMU-Pro

    HeyGen Voice—
    MiniMax M378.1%
    Source

    Not directly comparable

  • VideoMMMU

    HeyGen Voice—
    MiniMax M384.6%
    Source

    Not directly comparable

  • Video-MME (with subtitle)

    HeyGen Voice—
    MiniMax M385.4%
    Source

    Not directly comparable

Knowledge

  • GPQA Diamond (Vals)

    HeyGen Voice—
    MiniMax M392.7%
    Source

    Not directly comparable

  • MMLU-Pro (Vals)

    HeyGen Voice—
    MiniMax M384.2%
    Source

    Not directly comparable

Math

  • USAMO 2026

    HeyGen Voice—
    MiniMax M385.7%
    Source

    Not directly comparable

27 public results · 0 shared

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Last updated October 14, 2026