GPT-6 Astra vs Kimi K3

Updated October 17, 2026. Rank says GPT-6 Astra is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

Decision reading

GPT-6 Astra has the higher public score, 83.88 versus 69.87, and the 90% score intervals do not overlap. 16 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A

GPT-6 Astra

OpenAI

83.88/100

Supported · Public rank #3

90% interval 79.4–88.3

Model B

Kimi K3

Moonshot AI

69.87/100

Supported · Public rank #18

90% interval 65.8–74.0

Shared results: 16
GPT-6 Astra only: 24
Kimi K3 only: 36
Like-for-like categories: 3 / 8

Supported: GPT-6 Astra and 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.

Coding work
Code generation, repair, and software-engineering tasks
GPT-6 Astra
GPT-6 Astra has the higher public coding point estimate, 75.5 to 58.9, with Supported evidence for both models. The conditional ranges do not establish rank confidence.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
GPT-6 Astra
GPT-6 Astra has the higher public agentic point estimate, 74.8 to 69.4, with Supported evidence for both models. The conditional ranges do not establish rank confidence.
Confidence: limited
Chat turn cost
1K fresh input + 500 output tokens
Kimi K3
Kimi K3 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

Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Kimi K3
Kimi K3 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Repository review cost
50K fresh input + 3K output tokens
Kimi K3
Kimi K3 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Long documents
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documented

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.

75.5GPT-6 Astra58.9Kimi K3

Like-for-like · BenchAlign v5.8

GPT-6 Astra has the higher coding point estimate. Conditional score ranges do not establish rank confidence.

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

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.

ARC-AGI-2Reasoning
Normalized gap 34.6
GPT-6 Astra:95%
Kimi K3:60.4%
GPT-6 Astra source Kimi K3 source
AutomationBenchAgentic
Normalized gap 10.6
GPT-6 Astra:41.4%
Kimi K3:30.8%
GPT-6 Astra source Kimi K3 source
GPQAKnowledge
Normalized gap 2.5
GPT-6 Astra:96%
Kimi K3:93.5%
GPT-6 Astra source Kimi K3 source
BrowseCompAgentic
Normalized gap 0.3
GPT-6 Astra:91.5%
Kimi K3:91.2%
GPT-6 Astra source Kimi K3 source

Bars run 0–100 on each benchmark’s normalized display scale

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

Like-for-like

GPT-6 Astra: 74.8; Supported · #7/128
Kimi K3: 69.4; Supported · #10/128
Basis: BenchAlign v5.8 lane · 14 vs 15 public rows
Reading: GPT-6 Astra leads · intervals overlap

Coding

Like-for-like

GPT-6 Astra: 75.5; Supported · #4/150
Kimi K3: 58.9; Supported · #22/150
Basis: BenchAlign v5.8 lane · 6 vs 15 public rows
Reading: GPT-6 Astra leads · intervals overlap

Knowledge

Like-for-like

GPT-6 Astra: 86.2; Supported · #3/184
Kimi K3: 68.8; Supported · #21/184
Basis: BenchAlign v5.8 lane · 7 vs 6 public rows
Reading: GPT-6 Astra leads

Reasoning

Directional only

GPT-6 Astra: 93.3; #1/28
Kimi K3: 70.0; #21/28
Basis: Provisional lane · 2 vs 1 weighted rows
Reading: Directional only

Multimodal

Not comparable

GPT-6 Astra: 87.3; Unranked · 3 rankable rows
Kimi K3: 92.6; #1/54
Basis: Provisional lane · 0 vs 3 weighted rows
Reading: Not comparable

Multilingual

Not comparable

GPT-6 Astra: Not ranked
Kimi K3: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Instruction following

Not comparable

GPT-6 Astra: Not ranked
Kimi K3: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Math

Not comparable

GPT-6 Astra: 97.3; Unranked · 2 rankable rows
Kimi K3: Not ranked
Basis: Provisional lane · 2 vs 0 weighted rows
Reading: Not comparable

Category scores with the server-provided evidence basis for GPT-6 Astra and Kimi K3
Category	GPT-6 Astra	Kimi K3	Basis	Reading
Agentic	74.8Supported · #7/128	69.4Supported · #10/128	Like-for-likeBenchAlign v5.8 lane · 14 vs 15 public rows	GPT-6 Astra leads · intervals overlap
Coding	75.5Supported · #4/150	58.9Supported · #22/150	Like-for-likeBenchAlign v5.8 lane · 6 vs 15 public rows	GPT-6 Astra leads · intervals overlap
Knowledge	86.2Supported · #3/184	68.8Supported · #21/184	Like-for-likeBenchAlign v5.8 lane · 7 vs 6 public rows	GPT-6 Astra leads
Reasoning	93.3#1/28	70.0#21/28	Directional onlyProvisional lane · 2 vs 1 weighted rows	Directional only
Multimodal	87.3Unranked · 3 rankable rows	92.6#1/54	Not comparableProvisional lane · 0 vs 3 weighted 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	97.3Unranked · 2 rankable rows	Not ranked	Not comparableProvisional lane · 2 vs 0 weighted rows	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

GPT-6 Astra: $0.035; Fits in one request
Kimi K3: $0.0105; Fits in one request

Kimi K3 has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

GPT-6 Astra: $0.65; Fits in one request
Kimi K3: $0.195; Fits in one request

Kimi K3 has the lower modeled cost

Costs use the listed standard API rates.

Cache-heavy agent loop

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

GPT-6 Astra: $0.9; Fits in one request
Kimi K3: $0.27; Fits in one request

Kimi K3 has the lower modeled cost

Costs use the listed standard API rates.

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.

SpecificationGPT-6 AstraKimi K3

Context window

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

GPT-6 Astra

1.05M

OpenAI GPT-6 Astra model documentation

Kimi K3

1.05M

API model ID

GPT-6 Astra

gpt-6-astra

OpenAI GPT-6 Astra model 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.

GPT-6 Astra

$1 per 1M cached input tokens

OpenAI GPT-6 Astra model documentation

Kimi K3

$0.3 per 1M cached input tokens

Documented inputs

GPT-6 Astra

text, image

OpenAI GPT-6 Astra model documentation

Kimi K3

Not sourced

Documented outputs

GPT-6 Astra

text

OpenAI GPT-6 Astra model documentation

Kimi K3

Not sourced

Provider availability

GPT-6 Astra

Limited Availability · OpenAI Responses API, OpenAI Chat Completions API, ChatGPT Plus, Pro, Business, and Enterprise, Microsoft Azure, AWS Bedrock

OpenAI GPT-6 Astra model documentation

Kimi K3

Not sourced

Reasoning profile

GPT-6 Astra

Reasoning

Kimi K3

Reasoning

Weight access

GPT-6 Astra

Proprietary

Kimi K3

Pending

License

GPT-6 Astra

Proprietary

Kimi K3

Pending

Release date

GPT-6 Astra

2026-09-03

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: GPT-6 Astra has the higher public score, 83.88 versus 69.87, and the 90% score intervals do not overlap.
Workload cost: Repository review: $0.65 vs $0.195. Cache-heavy agent loop: $0.9 vs $0.27.
Context tradeoff: Both models list 1.05M.

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

Questions

Which is better, GPT-6 Astra or Kimi K3?

GPT-6 Astra has the higher public score, 83.88 versus 69.87, and the 90% score intervals do not overlap. That is the clearest overall quality signal in the current public data.

Which is better for coding, GPT-6 Astra or Kimi K3?

GPT-6 Astra has the higher public coding point estimate, 75.5 to 58.9, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

Which is better for agentic tasks, GPT-6 Astra or Kimi K3?

GPT-6 Astra has the higher public agentic tasks point estimate, 74.8 to 69.4, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

Which costs less, GPT-6 Astra or Kimi K3?

For the stated presets, chat costs $0.035 on GPT-6 Astra and $0.0105 on Kimi K3; repository review costs $0.65 and $0.195; the cache-heavy agent loop costs $0.9 and $0.27. Costs use the listed standard API rates.

Which has the larger context window, GPT-6 Astra or Kimi K3?

Both models list the same context window, 1.05M.

Benchmark evidence

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

Browse raw public benchmark evidence76 rows

Agentic

BrowseComp
GPT-6 Astra91.5%
Source
Kimi K391.2%
Source
GPT-6 Astra leads this result
OSWorld 2.0
GPT-6 Astra72.6%
Source
Kimi K3—
Not directly comparable
Terminal-Bench 4.0
GPT-6 Astra57.90%
Source
Kimi K3—
Not directly comparable
Terminal-Bench-Science 0.1
GPT-6 Astra64.6%
Source
Kimi K3—
Not directly comparable
ExploitGym
GPT-6 Astra42.4%
Source
Kimi K3—
Not directly comparable
Agents' Last Exam
GPT-6 Astra59.3%
Source
Kimi K3—
Not directly comparable
AutomationBench
GPT-6 Astra41.4%
Source
Kimi K330.8%
Source
GPT-6 Astra leads this result
HLE w/ tools
GPT-6 Astra57.2%
Source
Kimi K3—
Not directly comparable
Terminal-Bench 2.1 (Vals)
GPT-6 Astra87.3%
Source
Kimi K380.9%
Source
GPT-6 Astra leads this result
ApprenticeBench
Shared source
GPT-6 Astra68%
Kimi K318%
GPT-6 Astra leads this result
CWE-bench v1
GPT-6 Astra68.0%
Source
Kimi K3—
Not directly comparable
Hermes Index
Shared source
GPT-6 Astra56.3%
Kimi K339.2%
GPT-6 Astra leads this result
Hermes Bench
Shared source
GPT-6 Astra73.7%
Kimi K371.5%
GPT-6 Astra leads this result
MazeBench
GPT-6 Astra23%
Source
Kimi K31%
Source
GPT-6 Astra leads this result
Terminal-Bench 2.1
GPT-6 Astra—
Kimi K388.3%
Source
Not directly comparable
DeepSearchQA
GPT-6 Astra—
Kimi K395.0%
Source
Not directly comparable
Toolathlon-Verified
GPT-6 Astra—
Kimi K373.2%
Source
Not directly comparable
MCP Atlas
GPT-6 Astra—
Kimi K384.2%
Source
Not directly comparable
JobBench
GPT-6 Astra—
Kimi K352.9%
Source
Not directly comparable
APEX-Agents
GPT-6 Astra—
Kimi K337.6%
Source
Not directly comparable
SpreadsheetBench 2
GPT-6 Astra—
Kimi K334.8%
Source
Not directly comparable
DECK-Bench
GPT-6 Astra—
Kimi K373.5%
Source
Not directly comparable

Coding

DeepSWE
GPT-6 Astra74.1%
Source
Kimi K367.5%
Source
GPT-6 Astra leads this result
FrontierCode 1.1 Main
GPT-6 Astra53.3%
Source
Kimi K3—
Not directly comparable
FrontierCode 1.1 Extended
GPT-6 Astra64.5%
Source
Kimi K3—
Not directly comparable
FrontierSWE v2
Shared source
GPT-6 Astra65.5%
Kimi K325.9%
GPT-6 Astra leads this result
PostTrainBench v1.1
GPT-6 Astra44.3%
Source
Kimi K332.0%
Source
GPT-6 Astra leads this result
Bug Hunt Bench
Shared source
GPT-6 Astra45.0 fixes
Kimi K321.0 fixes
GPT-6 Astra leads this result
CursorBench 3.2
GPT-6 Astra—
Kimi K360.8%
Source
Not directly comparable
FrontierSWE
GPT-6 Astra—
Kimi K381.2%
Source
Not directly comparable
ProgramBench
GPT-6 Astra—
Kimi K377.8%
Source
Not directly comparable
Kimi Code Bench v2
GPT-6 Astra—
Kimi K372.9%
Source
Not directly comparable
sweMarathon
GPT-6 Astra—
Kimi K342%
Source
Not directly comparable
PostTrain Bench
GPT-6 Astra—
Kimi K336.6%
Source
Not directly comparable
MLS-Bench Lite
GPT-6 Astra—
Kimi K348.3%
Source
Not directly comparable
VulcanBench v3
GPT-6 Astra—
Kimi K373.7%
Source
Not directly comparable
OpenHarmony Bench
GPT-6 Astra—
Kimi K357.3%
Source
Not directly comparable
LiveCodeBench (Vals)
GPT-6 Astra—
Kimi K387.2%
Source
Not directly comparable
SWE-bench (Vals)
GPT-6 Astra—
Kimi K393.4%
Source
Not directly comparable

Reasoning

STEMBench
GPT-6 Astra2.81
Source
Kimi K3—
Not directly comparable
ARC-AGI-1
GPT-6 Astra98.50%
Source
Kimi K394.50%
Source
GPT-6 Astra leads this result
ARC-AGI-2
GPT-6 Astra95%
Source
Kimi K360.4%
Source
GPT-6 Astra leads this result
ARC-AGI-3
GPT-6 Astra62.7%
Source
Kimi K3—
Not directly comparable
GeneBench-Pro
GPT-6 Astra37.8%
Source
Kimi K3—
Not directly comparable
MRCR v2 256K-512K
GPT-6 Astra100.0%
Source
Kimi K3—
Not directly comparable
MRCR v2 512K-1M
GPT-6 Astra96.3%
Source
Kimi K3—
Not directly comparable
GraphWalks BFS 256K–1M
GPT-6 Astra71.8%
Source
Kimi K3—
Not directly comparable

Multimodal

ScreenSpot Pro
GPT-6 Astra92.7%
Source
Kimi K3—
Not directly comparable
BenchCAD Vision2Code (tools)
GPT-6 Astra0.959
Source
Kimi K3—
Not directly comparable
OfficeQA Pro
GPT-6 Astra—
Kimi K363.3%
Source
Not directly comparable
MMMU-Pro
GPT-6 Astra—
Kimi K381.6%
Source
Not directly comparable
MMMU-Pro w/ Python
GPT-6 Astra—
Kimi K383.4%
Source
Not directly comparable
CharXiv w/o tools
GPT-6 Astra—
Kimi K384.8%
Source
Not directly comparable
CharXiv
GPT-6 Astra—
Kimi K391.3%
Source
Not directly comparable
MathVision
GPT-6 Astra—
Kimi K394.3%
Source
Not directly comparable
MathVision w/ Python
GPT-6 Astra—
Kimi K397.8%
Source
Not directly comparable
BabyVision w/ Python
GPT-6 Astra—
Kimi K385.7%
Source
Not directly comparable
ZeroBench
GPT-6 Astra—
Kimi K323.0%
Source
Not directly comparable
ZeroBench w/ Python
GPT-6 Astra—
Kimi K341.0%
Source
Not directly comparable
WorldVQA ForceAnswer
GPT-6 Astra—
Kimi K351.0%
Source
Not directly comparable
OmniDocBench
GPT-6 Astra—
Kimi K391.1%
Source
Not directly comparable
PerceptionBench
GPT-6 Astra—
Kimi K358.5%
Source
Not directly comparable

Knowledge

GPQA
GPT-6 Astra96%
Source
Kimi K393.5%
Source
GPT-6 Astra leads this result
GPQA-D
GPT-6 Astra96.0%
Source
Kimi K393.5%
Source
GPT-6 Astra leads this result
HealthBench (raw)
GPT-6 Astra56.9%
Source
Kimi K3—
Not directly comparable
HealthBench (length-adjusted)
GPT-6 Astra58.3%
Source
Kimi K3—
Not directly comparable
HealthBench Professional
GPT-6 Astra64.7%
Source
Kimi K3—
Not directly comparable
HealthBench Professional (raw)
GPT-6 Astra68.2%
Source
Kimi K3—
Not directly comparable
HealthBench Hard
GPT-6 Astra36.6%
Source
Kimi K3—
Not directly comparable
HLE
GPT-6 Astra—
Kimi K356%
Source
Not directly comparable
HLE w/o tools
GPT-6 Astra—
Kimi K343.5%
Source
Not directly comparable
GPQA Diamond (Vals)
GPT-6 Astra—
Kimi K392.9%
Source
Not directly comparable
MMLU-Pro (Vals)
GPT-6 Astra—
Kimi K388.0%
Source
Not directly comparable

Instruction following

Gray Swan IPI (15 attempts)
Shared source
GPT-6 Astra8.5%
Kimi K352.7%
GPT-6 Astra leads this result

Math

FrontierMath v2 (Tier 4)
GPT-6 Astra97.600%
Source
Kimi K3—
Not directly comparable
FrontierMath v2 (Tiers 1-3)
GPT-6 Astra93.684%
Source
Kimi K3—
Not directly comparable

76 public results · 16 shared

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Last updated October 17, 2026

GPT-6 Astra vs Kimi K3

Decision reading

Which one for your work

Coding work

Agentic work

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

Long documents

Which one for a specific job

What is actually comparable

Shape of the matched evidence

Category results, on a stated basis

Agentic

Coding

Knowledge

Reasoning

Multimodal

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, GPT-6 Astra or Kimi K3?

Which is better for coding, GPT-6 Astra or Kimi K3?

Which is better for agentic tasks, GPT-6 Astra or Kimi K3?

Which costs less, GPT-6 Astra or Kimi K3?

Which has the larger context window, GPT-6 Astra or Kimi K3?

Benchmark evidence

Agentic

Coding

Reasoning

Multimodal

Knowledge

Instruction following

Math

Related comparisons

Watch GPT-6 Astra vs Kimi K3