Model A

LG AI Research

—

Evidence status unavailable

90% interval unavailable

K-EXAONE 2.0 vs Kimi K3

Updated September 10, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Model B

Kimi K3

Moonshot AI

74.82/100

Supported · Public rank #8

90% interval 71.4–78.2

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.

2 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

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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
K-EXAONE 2.0 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
K-EXAONE 2.0 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
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.

13 K-EXAONE 2.0 only

2 Shared

41 Kimi K3 only

Shared results: 2
K-EXAONE 2.0 only: 13
Kimi K3 only: 41
Like-for-like categories: 0 / 8

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign 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

K-EXAONE 2.0: Not ranked
Kimi K3: 71.9; Supported · #4/152
Basis: BenchAlign lane · 2 vs 11 public rows
Reading: Not comparable

Coding

Not comparable

K-EXAONE 2.0: Not ranked
Kimi K3: 68.0; Supported · #6/151
Basis: BenchAlign lane · 3 vs 13 public rows
Reading: Not comparable

Reasoning

Not comparable

K-EXAONE 2.0: Not ranked
Kimi K3: 78.5; #3/20
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Knowledge

Not comparable

K-EXAONE 2.0: Not ranked
Kimi K3: 72.0; Supported · #8/183
Basis: BenchAlign lane · 4 vs 6 public rows
Reading: Not comparable

Math

Not comparable

K-EXAONE 2.0: Not ranked
Kimi K3: Not ranked
Basis: Provisional lane · 2 vs 0 weighted rows
Reading: Not comparable

Multilingual

Not comparable

K-EXAONE 2.0: Not ranked
Kimi K3: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Multimodal

Not comparable

K-EXAONE 2.0: Not ranked
Kimi K3: 89.5; #1/48
Basis: Provisional lane · 0 vs 3 weighted rows
Reading: Not comparable

Instruction following

Not comparable

K-EXAONE 2.0: Not ranked
Kimi K3: Not ranked
Basis: Provisional lane · 1 vs 0 weighted rows
Reading: Not comparable

Category scores with the server-provided evidence basis for K-EXAONE 2.0 and Kimi K3
Category	K-EXAONE 2.0	Kimi K3	Basis	Reading
Agentic	Not ranked	71.9Supported · #4/152	Not comparableBenchAlign lane · 2 vs 11 public rows	Not comparable
Coding	Not ranked	68.0Supported · #6/151	Not comparableBenchAlign lane · 3 vs 13 public rows	Not comparable
Reasoning	Not ranked	78.5#3/20	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable
Knowledge	Not ranked	72.0Supported · #8/183	Not comparableBenchAlign lane · 4 vs 6 public rows	Not comparable
Math	Not ranked	Not ranked	Not comparableProvisional lane · 2 vs 0 weighted rows	Not comparable
Multilingual	Not ranked	Not ranked	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable
Multimodal	Not ranked	89.5#1/48	Not comparableProvisional lane · 0 vs 3 weighted rows	Not comparable
Instruction following	Not ranked	Not ranked	Not comparableProvisional lane · 1 vs 0 weighted rows	Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

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.

HLE
Knowledge
K-EXAONE 2.0: 18.3%Kimi K3: 56%Normalized gap 37.7K-EXAONE 2.0 source Kimi K3 source

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

K-EXAONE 2.0: Self-hosted; infrastructure cost varies; Fits in one request
Kimi K3: $0.0105; Fits in one request

K-EXAONE 2.0 has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

K-EXAONE 2.0: Self-hosted; infrastructure cost varies; Fits in one request
Kimi K3: $0.195; Fits in one request

K-EXAONE 2.0 has no comparable published API token rate.

Cache-heavy agent loop

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

K-EXAONE 2.0: Self-hosted; infrastructure cost varies; Fits in one request; Cached-input rate unavailable
Kimi K3: $0.27; Fits in one request

K-EXAONE 2.0 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.

SpecificationK-EXAONE 2.0Kimi K3

Context window

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

K-EXAONE 2.0

262K

LG AI Research K-EXAONE 2.0 model card

Kimi K3

1.05M

API model ID

K-EXAONE 2.0

LGAI-EXAONE/K-EXAONE-2.0-750B-A37B

LG AI Research K-EXAONE 2.0 model card

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.

K-EXAONE 2.0

No comparable hosted API rate

LG AI Research K-EXAONE 2.0 model card

Kimi K3

$0.3 per 1M cached input tokens

Documented inputs

K-EXAONE 2.0

Not sourced

Kimi K3

Not sourced

Documented outputs

K-EXAONE 2.0

Not sourced

Kimi K3

Not sourced

Provider availability

K-EXAONE 2.0

Not sourced

Kimi K3

Not sourced

Reasoning profile

K-EXAONE 2.0

Reasoning

Kimi K3

Reasoning

Weight access

K-EXAONE 2.0

Open Weight

Kimi K3

Pending

License

K-EXAONE 2.0

Open Weight

Kimi K3

Pending

Release date

K-EXAONE 2.0

2026-07-31

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

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 evidence56 rows

Agentic

Terminal-Bench 2.1
K-EXAONE 2.043.8%
Source
Kimi K3—
Not directly comparable
Claw-Eval
K-EXAONE 2.077.7%
Source
Kimi K3—
Not directly comparable
Terminal-Bench 2.0
K-EXAONE 2.0—
Kimi K388.3%
Source
Not directly comparable
BrowseComp
K-EXAONE 2.0—
Kimi K391.2%
Source
Not directly comparable
DeepSearchQA
K-EXAONE 2.0—
Kimi K395.0%
Source
Not directly comparable
Toolathlon-Verified
K-EXAONE 2.0—
Kimi K373.2%
Source
Not directly comparable
MCP Atlas
K-EXAONE 2.0—
Kimi K384.2%
Source
Not directly comparable
AutomationBench
K-EXAONE 2.0—
Kimi K330.8%
Source
Not directly comparable
JobBench
K-EXAONE 2.0—
Kimi K352.9%
Source
Not directly comparable
APEX-Agents
K-EXAONE 2.0—
Kimi K337.6%
Source
Not directly comparable
SpreadsheetBench 2
K-EXAONE 2.0—
Kimi K334.8%
Source
Not directly comparable
DECK-Bench
K-EXAONE 2.0—
Kimi K373.5%
Source
Not directly comparable
Terminal-Bench 2.1 (Vals)
K-EXAONE 2.0—
Kimi K380.9%
Source
Not directly comparable

Coding

SciCode
K-EXAONE 2.037.4%
Source
Kimi K3—
Not directly comparable
SWE-bench Verified
K-EXAONE 2.068.2%
Source
Kimi K3—
Not directly comparable
Terminal-Bench 2.1
K-EXAONE 2.043.8%
Source
Kimi K3—
Not directly comparable
DeepSWE
K-EXAONE 2.0—
Kimi K367.5%
Source
Not directly comparable
cursorBench32
K-EXAONE 2.0—
Kimi K360.8%
Source
Not directly comparable
FrontierSWE
K-EXAONE 2.0—
Kimi K381.2%
Source
Not directly comparable
ProgramBench
K-EXAONE 2.0—
Kimi K377.8%
Source
Not directly comparable
Kimi Code Bench v2
K-EXAONE 2.0—
Kimi K372.9%
Source
Not directly comparable
sweMarathon
K-EXAONE 2.0—
Kimi K342%
Source
Not directly comparable
PostTrain Bench
K-EXAONE 2.0—
Kimi K336.6%
Source
Not directly comparable
MLS-Bench Lite
K-EXAONE 2.0—
Kimi K348.3%
Source
Not directly comparable
VulcanBench v3
K-EXAONE 2.0—
Kimi K373.7%
Source
Not directly comparable
OpenHarmony Bench
K-EXAONE 2.0—
Kimi K357.3%
Source
Not directly comparable
FrontierSWE v2
K-EXAONE 2.0—
Kimi K325.9%
Source
Not directly comparable
LiveCodeBench (Vals)
K-EXAONE 2.0—
Kimi K387.2%
Source
Not directly comparable
SWE-bench (Vals)
K-EXAONE 2.0—
Kimi K393.4%
Source
Not directly comparable

Knowledge

MMLU-Pro
K-EXAONE 2.083.5%
Source
Kimi K3—
Not directly comparable
GPQA-D
K-EXAONE 2.082.2%
Source
Kimi K393.5%
Source
Kimi K3 leads this result
HLE
K-EXAONE 2.018.3%
Source
Kimi K356%
Source
Kimi K3 leads this result
MMMLU
K-EXAONE 2.086.6%
Source
Kimi K3—
Not directly comparable
GPQA
K-EXAONE 2.0—
Kimi K393.5%
Source
Not directly comparable
HLE w/o tools
K-EXAONE 2.0—
Kimi K343.5%
Source
Not directly comparable
GPQA Diamond (Vals)
K-EXAONE 2.0—
Kimi K392.9%
Source
Not directly comparable
MMLU-Pro (Vals)
K-EXAONE 2.0—
Kimi K388.0%
Source
Not directly comparable

Math

AIME26
K-EXAONE 2.092.3%
Source
Kimi K3—
Not directly comparable
HMMT Feb 2026
K-EXAONE 2.078.4%
Source
Kimi K3—
Not directly comparable
IMOAnswerBench
K-EXAONE 2.078.6%
Source
Kimi K3—
Not directly comparable

Multilingual

PolyMath
K-EXAONE 2.071.3%
Source
Kimi K3—
Not directly comparable

Multimodal

OfficeQA Pro
K-EXAONE 2.0—
Kimi K363.3%
Source
Not directly comparable
MMMU-Pro
K-EXAONE 2.0—
Kimi K381.6%
Source
Not directly comparable
MMMU-Pro w/ Python
K-EXAONE 2.0—
Kimi K383.4%
Source
Not directly comparable
CharXiv w/o tools
K-EXAONE 2.0—
Kimi K384.8%
Source
Not directly comparable
CharXiv
K-EXAONE 2.0—
Kimi K391.3%
Source
Not directly comparable
MathVision
K-EXAONE 2.0—
Kimi K394.3%
Source
Not directly comparable
MathVision w/ Python
K-EXAONE 2.0—
Kimi K397.8%
Source
Not directly comparable
BabyVision w/ Python
K-EXAONE 2.0—
Kimi K385.7%
Source
Not directly comparable
ZeroBench
K-EXAONE 2.0—
Kimi K323.0%
Source
Not directly comparable
ZeroBench w/ Python
K-EXAONE 2.0—
Kimi K341.0%
Source
Not directly comparable
WorldVQA ForceAnswer
K-EXAONE 2.0—
Kimi K351.0%
Source
Not directly comparable
OmniDocBench
K-EXAONE 2.0—
Kimi K391.1%
Source
Not directly comparable
PerceptionBench
K-EXAONE 2.0—
Kimi K358.5%
Source
Not directly comparable

Instruction following

IFEval
K-EXAONE 2.092.4%
Source
Kimi K3—
Not directly comparable
IFBench
K-EXAONE 2.072.6%
Source
Kimi K3—
Not directly comparable

Frequently asked questions

Which is better, K-EXAONE 2.0 or Kimi K3?

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, K-EXAONE 2.0 or Kimi K3?

K-EXAONE 2.0 is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, K-EXAONE 2.0 or Kimi K3?

K-EXAONE 2.0 is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, K-EXAONE 2.0 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, K-EXAONE 2.0 or Kimi K3?

Kimi K3 has the larger documented context window: 1.05M, compared with 262K.

Related comparisons

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Last updated September 10, 2026

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K-EXAONE 2.0 vs Kimi K3

Which one for your work

Long documents

Coding work

Agentic work

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

What is actually comparable

Category results, on a stated basis

Agentic

Coding

Reasoning

Knowledge

Math

Multilingual

Multimodal

Instruction following

Shape of the matched evidence

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

Benchmark evidence

Agentic

Coding

Knowledge

Math

Multilingual

Multimodal

Instruction following

Frequently asked questions

Which is better, K-EXAONE 2.0 or Kimi K3?

Which is better for coding, K-EXAONE 2.0 or Kimi K3?

Which is better for agentic tasks, K-EXAONE 2.0 or Kimi K3?

Which costs less, K-EXAONE 2.0 or Kimi K3?

Which has the larger context window, K-EXAONE 2.0 or Kimi K3?

Related comparisons

Watch K-EXAONE 2.0 vs Kimi K3