HeyGen Decision 1 vs Kimi K3

Updated November 13, 2026. We do not rank this pair: at least one has no public score. Public scores include evidence status and uncertainty.

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 Decision 1

HeyGen

—

Evidence status unavailable

90% interval unavailable

Model B

Kimi K3

Moonshot AI

68.45/100

Supported · Public rank #17

90% interval 64.0–72.9

API price per 1M tokens

HeyGen Decision 1: No comparable API price

Kimi K3: $3 input / $15 output

Context window

HeyGen Decision 1: 131072 tokens per model read

Kimi K3: 1.05M

Released

HeyGen Decision 1: November 13, 2026

Kimi K3: July 16, 2026

Shared results: 0
HeyGen Decision 1 only: 0
Kimi K3 only: 59
Like-for-like categories: 0 / 8

Supported: Kimi K3How 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
Kimi K3
Kimi K3 has the larger documented context window.
Confidence: documented

Show secondary and unsupported calls

Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
HeyGen Decision 1 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 Decision 1 is not ranked on the public lane for agentic, so no winner is named for agentic.
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
The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. HeyGen Decision 1 does not fit this workload in one request. HeyGen Decision 1 has no comparable published API token rate.
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.

Pick the job you would use them for

The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.

—HeyGen Decision 156.2Kimi K3

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 leaderboard Shortlist models for this job

Same basis rules as the category table below

Or describe your own job

The LLM Selector reads what you need a model for and returns a shortlist, ranked in the same order the job pages publish.

What do you need a model for?

Describe the task and constraints. This selector recommends models; it cannot carry out the task or access your files and accounts.

We keep what you type here, drafts included, for 180 days, and after that only the job and requirements read from it. Nothing is tied to your IP address or account. Leave out names and other personal details. Privacy

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, reasoning, multimodal, 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 Decision 1: Not ranked
Kimi K3: 65.7; Supported · #16/135
Basis: BenchAlign v5.8 lane · 0 vs 18 public rows
Reading: Not comparable

Coding

Not comparable

HeyGen Decision 1: Not ranked
Kimi K3: 56.2; Supported · #24/162
Basis: BenchAlign v5.8 lane · 0 vs 18 public rows
Reading: Not comparable

Reasoning

Not comparable

HeyGen Decision 1: Not ranked
Kimi K3: 65.5; Supported · #21/160
Basis: BenchAlign v5.8 lane · 0 vs 2 public rows
Reading: Not comparable

Multimodal

Not comparable

HeyGen Decision 1: Not ranked
Kimi K3: 67.7; Estimated · #19/67
Basis: BenchAlign v5.8 lane · 0 vs 14 public rows
Reading: Not comparable

Knowledge

Not comparable

HeyGen Decision 1: Not ranked
Kimi K3: 67.7; Supported · #20/180
Basis: BenchAlign v5.8 lane · 0 vs 6 public rows
Reading: Not comparable

Multilingual

Not comparable

HeyGen Decision 1: Not ranked
Kimi K3: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Instruction following

Not comparable

HeyGen Decision 1: Not ranked
Kimi K3: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Math

Not comparable

HeyGen Decision 1: Not ranked
Kimi K3: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Category scores with the server-provided evidence basis for HeyGen Decision 1 and Kimi K3
Category	HeyGen Decision 1	Kimi K3	Basis	Reading
Agentic	Not ranked	65.7Supported · #16/135	Not comparableBenchAlign v5.8 lane · 0 vs 18 public rows	Not comparable
Coding	Not ranked	56.2Supported · #24/162	Not comparableBenchAlign v5.8 lane · 0 vs 18 public rows	Not comparable
Reasoning	Not ranked	65.5Supported · #21/160	Not comparableBenchAlign v5.8 lane · 0 vs 2 public rows	Not comparable
Multimodal	Not ranked	67.7Estimated · #19/67	Not comparableBenchAlign v5.8 lane · 0 vs 14 public rows	Not comparable
Knowledge	Not ranked	67.7Supported · #20/180	Not comparableBenchAlign v5.8 lane · 0 vs 6 public rows	Not comparable
Multilingual	Not ranked	Not ranked	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable
Instruction following	Not ranked	Not ranked	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable
Math	Not ranked	Not ranked	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, reasoning, multimodal, 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 Decision 1: API rate not published; Fits in one request
Kimi K3: $0.0105; Fits in one request

HeyGen Decision 1 has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

HeyGen Decision 1: API rate not published; Fits in one request
Kimi K3: $0.195; Fits in one request

HeyGen Decision 1 has no comparable published API token rate.

Cache-heavy agent loop

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

HeyGen Decision 1: API rate not published; Does not fit in one request; Cached-input rate unavailable
Kimi K3: $0.27; Fits in one request

HeyGen Decision 1 does not fit this workload in one request. HeyGen Decision 1 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.

SpecificationHeyGen Decision 1Kimi K3

Context window

Maximum documented context; output-token limits may be lower.

HeyGen Decision 1

131072 tokens per model read

HeyGen Decision API documentation

Kimi K3

1.05M

API model ID

HeyGen Decision 1

heygen-decision-1

HeyGen Decision API documentation

Kimi K3

Not sourced

Cached-input rate

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

HeyGen Decision 1

No comparable hosted API rate

HeyGen Decision API documentation

Kimi K3

$0.3 per 1M cached input tokens

Documented inputs

HeyGen Decision 1

text, image, video

HeyGen Decision API documentation

Kimi K3

text, image, video

Kimi-K3 model card

Documented outputs

HeyGen Decision 1

typed JSON

HeyGen Decision API documentation

Kimi K3

text

Kimi-K3 model card

Provider availability

HeyGen Decision 1

Generally Available · HeyGen API

HeyGen Decision API documentation

Kimi K3

Not sourced

Reasoning profile

HeyGen Decision 1

Unspecified

Kimi K3

Reasoning

Weight access

HeyGen Decision 1

Proprietary

Kimi K3

Open Weight

License

HeyGen Decision 1

Proprietary

Kimi K3

Open Weight

Release date

HeyGen Decision 1

2026-11-13

Kimi K3

2026-07-16

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: Kimi K3 has the larger documented window (1.05M).

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

Questions

Which is better, HeyGen Decision 1 or Kimi K3?

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 Decision 1 or Kimi K3?

HeyGen Decision 1 is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, HeyGen Decision 1 or Kimi K3?

HeyGen Decision 1 is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, HeyGen Decision 1 or Kimi K3?

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 Decision 1 or Kimi K3?

Kimi K3 has the larger documented context window: 1.05M, compared with 131072 tokens per model read.

Self-host vs API cost

Estimates at 50,000 req/day · 1000 tokens/req average.

HeyGen Decision 1

API / moNo API price on file

Self-host / moNot listed

Break-even—

Proprietary model — self-hosting not applicable.

Kimi K3

API / mo$13,500

Self-host / mo$57,606

Break-evenNot reached at 70% load

Model the full break-even

Benchmark evidence

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

Browse raw public benchmark evidence59 rows

Agentic

Finch
HeyGen Decision 1—
Kimi K377.3%
Source
Not directly comparable
b3 Agent Security
HeyGen Decision 1—
Kimi K388.0%
Source
Not directly comparable
Cyber Misuse Refusal
HeyGen Decision 1—
Kimi K394.0%
Source
Not directly comparable
Terminal-Bench 2.1
HeyGen Decision 1—
Kimi K388.3%
Source
Not directly comparable
BrowseComp
HeyGen Decision 1—
Kimi K391.2%
Source
Not directly comparable
DeepSearchQA
HeyGen Decision 1—
Kimi K395.0%
Source
Not directly comparable
Toolathlon-Verified
HeyGen Decision 1—
Kimi K373.2%
Source
Not directly comparable
MCP Atlas
HeyGen Decision 1—
Kimi K384.2%
Source
Not directly comparable
AutomationBench
HeyGen Decision 1—
Kimi K330.8%
Source
Not directly comparable
JobBench
HeyGen Decision 1—
Kimi K352.9%
Source
Not directly comparable
APEX-Agents
HeyGen Decision 1—
Kimi K337.6%
Source
Not directly comparable
SpreadsheetBench 2
HeyGen Decision 1—
Kimi K334.8%
Source
Not directly comparable
DECK-Bench
HeyGen Decision 1—
Kimi K373.5%
Source
Not directly comparable
Terminal-Bench 2.1 (Vals)
HeyGen Decision 1—
Kimi K380.9%
Source
Not directly comparable
ApprenticeBench
HeyGen Decision 1—
Kimi K318%
Source
Not directly comparable
Hermes Index
HeyGen Decision 1—
Kimi K339.2%
Source
Not directly comparable
Hermes Bench
HeyGen Decision 1—
Kimi K371.5%
Source
Not directly comparable
MazeBench
HeyGen Decision 1—
Kimi K31%
Source
Not directly comparable

Coding

ScarfBench
HeyGen Decision 1—
Kimi K361.3%
Source
Not directly comparable
DeepSWE
HeyGen Decision 1—
Kimi K367.5%
Source
Not directly comparable
CursorBench 3.2
HeyGen Decision 1—
Kimi K360.8%
Source
Not directly comparable
FrontierSWE
HeyGen Decision 1—
Kimi K381.2%
Source
Not directly comparable
ProgramBench
HeyGen Decision 1—
Kimi K377.8%
Source
Not directly comparable
Kimi Code Bench v2
HeyGen Decision 1—
Kimi K372.9%
Source
Not directly comparable
sweMarathon
HeyGen Decision 1—
Kimi K342%
Source
Not directly comparable
PostTrainBench (lab runs)
HeyGen Decision 1—
Kimi K336.6%
Source
Not directly comparable
MLS-Bench Lite
HeyGen Decision 1—
Kimi K348.3%
Source
Not directly comparable
VulcanBench v3
HeyGen Decision 1—
Kimi K373.7%
Source
Not directly comparable
OpenHarmony Bench v1.0
HeyGen Decision 1—
Kimi K357.3%
Source
Not directly comparable
FrontierSWE v2
HeyGen Decision 1—
Kimi K325.9%
Source
Not directly comparable
LiveCodeBench (Vals)
HeyGen Decision 1—
Kimi K387.2%
Source
Not directly comparable
SWE-bench (Vals)
HeyGen Decision 1—
Kimi K393.4%
Source
Not directly comparable
PostTrainBench v1.1
HeyGen Decision 1—
Kimi K332.0%
Source
Not directly comparable
Bug Hunt Bench
HeyGen Decision 1—
Kimi K321.0 fixes
Source
Not directly comparable
FrontierCode 2.0
HeyGen Decision 1—
Kimi K317.7%
Source
Not directly comparable
PostTrainBench
HeyGen Decision 1—
Kimi K331.5%
Source
Not directly comparable

Reasoning

ARC-AGI-1
HeyGen Decision 1—
Kimi K394.50%
Source
Not directly comparable
ARC-AGI-2
HeyGen Decision 1—
Kimi K360.4%
Source
Not directly comparable

Multimodal

ExtractBench (LlamaIndex)
HeyGen Decision 1—
Kimi K383.17%
Source
Not directly comparable
OfficeQA Pro
HeyGen Decision 1—
Kimi K363.3%
Source
Not directly comparable
MMMU-Pro
HeyGen Decision 1—
Kimi K381.6%
Source
Not directly comparable
MMMU-Pro w/ Python
HeyGen Decision 1—
Kimi K383.4%
Source
Not directly comparable
CharXiv w/o tools
HeyGen Decision 1—
Kimi K384.8%
Source
Not directly comparable
CharXiv
HeyGen Decision 1—
Kimi K391.3%
Source
Not directly comparable
MathVision
HeyGen Decision 1—
Kimi K394.3%
Source
Not directly comparable
MathVision w/ Python
HeyGen Decision 1—
Kimi K397.8%
Source
Not directly comparable
BabyVision w/ Python
HeyGen Decision 1—
Kimi K385.7%
Source
Not directly comparable
ZeroBench
HeyGen Decision 1—
Kimi K323.0%
Source
Not directly comparable
ZeroBench w/ Python
HeyGen Decision 1—
Kimi K341.0%
Source
Not directly comparable
WorldVQA ForceAnswer
HeyGen Decision 1—
Kimi K351.0%
Source
Not directly comparable
OmniDocBench
HeyGen Decision 1—
Kimi K391.1%
Source
Not directly comparable
PerceptionBench
HeyGen Decision 1—
Kimi K358.5%
Source
Not directly comparable

Knowledge

GPQA
HeyGen Decision 1—
Kimi K393.5%
Source
Not directly comparable
GPQA-D
HeyGen Decision 1—
Kimi K393.5%
Source
Not directly comparable
HLE
HeyGen Decision 1—
Kimi K356%
Source
Not directly comparable
HLE w/o tools
HeyGen Decision 1—
Kimi K343.5%
Source
Not directly comparable
GPQA Diamond (Vals)
HeyGen Decision 1—
Kimi K392.9%
Source
Not directly comparable
MMLU-Pro (Vals)
HeyGen Decision 1—
Kimi K388.0%
Source
Not directly comparable

Instruction following

Gray Swan IPI (15 attempts)
HeyGen Decision 1—
Kimi K352.7%
Source
Not directly comparable

59 public results · 0 shared

Related comparisons

Compare API pricing Read the methodology Open the model selector

Watch HeyGen Decision 1 vs Kimi K3

One weekly email when material rank, price, or benchmark evidence changes make this matchup worth revisiting.

Read a sample issue

Join 7,000+ subscribers.

Last updated November 13, 2026

HeyGen Decision 1 vs Kimi K3

Decision reading

Which one for your work

Long documents

Coding work

Agentic work

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

Which one for a specific job

Or describe your own job

What is actually comparable

Shape of the matched evidence

Category results, on a stated basis

Agentic

Coding

Reasoning

Multimodal

Knowledge

Multilingual

Instruction following

Math

What each workload costs

Chat turn

Repository review

Cache-heavy agent loop

Specification differences

Context window

API model ID

Cached-input rate

Documented inputs

Documented outputs

Provider availability

Reasoning profile

Weight access

License

Release date

If you already use one of these models

Questions

Which is better, HeyGen Decision 1 or Kimi K3?

Which is better for coding, HeyGen Decision 1 or Kimi K3?

Which is better for agentic tasks, HeyGen Decision 1 or Kimi K3?

Which costs less, HeyGen Decision 1 or Kimi K3?

Which has the larger context window, HeyGen Decision 1 or Kimi K3?

Self-host vs API cost

Benchmark evidence

Agentic

Coding

Reasoning

Multimodal

Knowledge

Instruction following

Related comparisons

Watch HeyGen Decision 1 vs Kimi K3