Knowledge
Directional only- GPT-6 Astra
- 96.0
- Kimi K2.5
- 56.9
- Weighted basis
- 1 vs 4 rows
- Reading
- Directional only
GPT-6 Astra vs Kimi K2.5
Updated September 3, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
GPT-6 Astra has the higher public score, 81.88 versus 58.81, and the 90% score intervals do not overlap.
3 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.
Long documents
Prompts that approach the documented context limit
GPT-6 Astra
GPT-6 Astra has the larger documented context window.
Confidence: documented
Chat turn cost
1K fresh input + 500 output tokens
Kimi K2.5
Kimi K2.5 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
Kimi K2.5
Kimi K2.5 has the lower estimated token cost for this stated workload. Kimi K2.5 has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback
Show secondary and unsupported calls
Repository review cost
50K fresh input + 3K output tokens
Kimi K2.5
Kimi K2.5 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
13 GPT-6 Astra only
3 Shared
42 Kimi K2.5 only
- Shared results
- 3
- GPT-6 Astra only
- 13
- Kimi K2.5 only
- 42
- Like-for-like categories
- 0 / 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.
Math
Directional only- GPT-6 Astra
- 97.6
- Kimi K2.5
- 60.6
- Weighted basis
- 1 vs 4 rows
- Reading
- Directional only
Agentic
Not comparable- GPT-6 Astra
- Not measured
- Kimi K2.5
- 55.0
- Weighted basis
- 0 vs 2 rows
- Reading
- Not comparable
Coding
Not comparable- GPT-6 Astra
- Not measured
- Kimi K2.5
- 59.4
- Weighted basis
- 0 vs 4 rows
- Reading
- Not comparable
Reasoning
Not comparable- GPT-6 Astra
- 95.0
- Kimi K2.5
- 61.0
- Weighted basis
- 1 vs 1 rows
- Reading
- Not comparable
Multilingual
Not comparable- GPT-6 Astra
- Not measured
- Kimi K2.5
- 82.3
- Weighted basis
- 0 vs 1 rows
- Reading
- Not comparable
Multimodal
Not comparable- GPT-6 Astra
- Not measured
- Kimi K2.5
- 78.5
- Weighted basis
- 0 vs 1 rows
- Reading
- Not comparable
Instruction following
Not comparable- GPT-6 Astra
- Not measured
- Kimi K2.5
- 93.9
- Weighted basis
- 0 vs 1 rows
- Reading
- Not comparable
| Category | GPT-6 Astra | Kimi K2.5 | Weighted basis | Reading |
|---|---|---|---|---|
| Knowledge | 96.0 | 56.9 | Directional only1 vs 4 rows | Directional only |
| Math | 97.6 | 60.6 | Directional only1 vs 4 rows | Directional only |
| Agentic | Not measured | 55.0 | Not comparable0 vs 2 rows | Not comparable |
| Coding | Not measured | 59.4 | Not comparable0 vs 4 rows | Not comparable |
| Reasoning | 95.0 | 61.0 | Not comparable1 vs 1 rows | Not comparable |
| Multilingual | Not measured | 82.3 | Not comparable0 vs 1 rows | Not comparable |
| Multimodal | Not measured | 78.5 | Not comparable0 vs 1 rows | Not comparable |
| Instruction following | Not measured | 93.9 | Not comparable0 vs 1 rows | 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.
FrontierMath v2 (Tier 4)
Math
GPQA
Knowledge
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 K2.5
- $0.0021
- Fits in one request
Kimi K2.5 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 K2.5
- $0.039
- Fits in one request
Kimi K2.5 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 K2.5
- $0.162
- Fits in one request
- Cached input priced at the published list-input rate
Kimi K2.5 has the lower modeled cost
Kimi K2.5 has no published cached-input rate, so cached tokens use its listed input rate.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationGPT-6 AstraKimi K2.5
Context window
Maximum documented context; output-token limits may be lower.
GPT-6 Astra
Kimi K2.5
256K
API model ID
GPT-6 Astra
gpt-6-astra
OpenAI GPT-6 Astra model documentationKimi K2.5
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 documentationKimi K2.5
Not published
Documented inputs
GPT-6 Astra
text, image
OpenAI GPT-6 Astra model documentationKimi K2.5
Not sourced
Documented outputs
GPT-6 Astra
Kimi K2.5
Not sourced
Provider availability
GPT-6 Astra
Limited Availability · OpenAI Responses API, ChatGPT Plus, Pro, Business, and Enterprise
OpenAI GPT-6 Astra model documentationKimi K2.5
Not sourced
Reasoning profile
GPT-6 Astra
Reasoning
Kimi K2.5
Non-Reasoning
Weight access
GPT-6 Astra
Proprietary
Kimi K2.5
Open Weight
License
GPT-6 Astra
Proprietary
Kimi K2.5
Open Weight
Release date
GPT-6 Astra
2026-09-03
Kimi K2.5
2026-02-01
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
- GPT-6 Astra has the higher public score, 81.88 versus 58.81, and the 90% score intervals do not overlap.
- Workload cost
- Repository review: $0.65 vs $0.039. Cache-heavy agent loop: $0.9 vs $0.162.
- Context tradeoff
- GPT-6 Astra has the larger documented window (1.05M).
Run the same representative tasks against both endpoints before changing production traffic.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
GPT-6 Astra
API / mo$45,000
Self-host / moNot listed
Break-even—
Proprietary model — self-hosting not applicable.
Kimi K2.5
API / mo$2,700
Self-host / mo$5,221
Break-even132M/day
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence58 rows
Agentic
OSWorld 2.0
GPT-6 Astra72.6%SourceKimi K2.5—Not directly comparable
Terminal-Bench 4.0
GPT-6 Astra57.70%SourceKimi K2.5—Not directly comparable
Terminal-Bench-Science 0.1
GPT-6 Astra64.6%SourceKimi K2.5—Not directly comparable
ExploitGym
GPT-6 Astra42.4%SourceKimi K2.5—Not directly comparable
Agents' Last Exam
GPT-6 Astra59.3%SourceKimi K2.5—Not directly comparable
Terminal-Bench 2.0
GPT-6 Astra—Kimi K2.550.8%SourceNot directly comparable
BrowseComp
GPT-6 Astra—Kimi K2.560.6%SourceNot directly comparable
Claw-Eval
GPT-6 Astra—Kimi K2.552.3%SourceNot directly comparable
QwenClawBench
GPT-6 Astra—Kimi K2.554.3%SourceNot directly comparable
τ³-bench results
GPT-6 Astra—Kimi K2.565.7%SourceNot directly comparable
DeepSearchQA
GPT-6 Astra—Kimi K2.577.1%SourceNot directly comparable
DeepPlanning
GPT-6 Astra—Kimi K2.514.4%SourceNot directly comparable
Toolathlon
GPT-6 Astra—Kimi K2.527.8%SourceNot directly comparable
MCP Atlas
GPT-6 Astra—Kimi K2.529.5%SourceNot directly comparable
MCP-Tasks
GPT-6 Astra—Kimi K2.559.1%SourceNot directly comparable
WideResearch
GPT-6 Astra—Kimi K2.572.7%SourceNot directly comparable
Gert Labs
GPT-6 Astra—Kimi K2.545.88%SourceNot directly comparable
ResearchClawBench
GPT-6 Astra—Kimi K2.514.0%SourceNot directly comparable
JobBench
GPT-6 Astra—Kimi K2.58.7%SourceNot directly comparable
Coding
deepSwe
GPT-6 Astra74.1%SourceKimi K2.5—Not directly comparable
SWE-bench Verified
GPT-6 Astra—Kimi K2.576.8%SourceNot directly comparable
SWE-bench Verified*
GPT-6 Astra—Kimi K2.570.8%SourceNot directly comparable
LiveCodeBench v6
GPT-6 Astra—Kimi K2.585.0%SourceNot directly comparable
SWE-bench Pro
GPT-6 Astra—Kimi K2.550.7%SourceNot directly comparable
SWE Multilingual
GPT-6 Astra—Kimi K2.573%SourceNot directly comparable
SWE-Rebench
GPT-6 Astra—Kimi K2.558.5%SourceNot directly comparable
React Native Evals
GPT-6 Astra—Kimi K2.577.2%SourceNot directly comparable
SciCode
GPT-6 Astra—Kimi K2.548.7%SourceNot directly comparable
Reasoning
ARC-AGI-2
GPT-6 Astra95%SourceKimi K2.5—Not directly comparable
ARC-AGI-3
GPT-6 Astra62.7%SourceKimi K2.5—Not directly comparable
MRCR v2 256K-512K
GPT-6 Astra100.0%SourceKimi K2.5—Not directly comparable
MRCR v2 512K-1M
GPT-6 Astra96.3%SourceKimi K2.5—Not directly comparable
LongBench v2
GPT-6 Astra—Kimi K2.561%SourceNot directly comparable
Knowledge
GPQA
GPT-6 Astra96%SourceKimi K2.587.6%SourceGPT-6 Astra leads this result
GPQA-D
GPT-6 Astra96.0%SourceKimi K2.587.6%SourceGPT-6 Astra leads this result
HealthBench Professional
GPT-6 Astra63.4%SourceKimi K2.5—Not directly comparable
HealthBench Hard
GPT-6 Astra36.3%SourceKimi K2.5—Not directly comparable
SuperGPQA
GPT-6 Astra—Kimi K2.569.2%SourceNot directly comparable
MMLU-Pro
GPT-6 Astra—Kimi K2.587.1%SourceNot directly comparable
MMLU-Pro (Arcee)
GPT-6 Astra—Kimi K2.587.1%SourceNot directly comparable
HLE
GPT-6 Astra—Kimi K2.530.1%SourceNot directly comparable
Math
FrontierMath v2 (Tier 4)
GPT-6 Astra97.600%SourceKimi K2.54.200%SourceGPT-6 Astra leads this result
AIME 2025
GPT-6 Astra—Kimi K2.596.1%SourceNot directly comparable
AIME26
GPT-6 Astra—Kimi K2.595.8%SourceNot directly comparable
AIME25 (Arcee)
GPT-6 Astra—Kimi K2.596.3%SourceNot directly comparable
HMMT Feb 2025
GPT-6 Astra—Kimi K2.595.4%SourceNot directly comparable
HMMT Nov 2025
GPT-6 Astra—Kimi K2.591.1%SourceNot directly comparable
HMMT Feb 2026
GPT-6 Astra—Kimi K2.587.1%SourceNot directly comparable
MMAnswerBench
GPT-6 Astra—Kimi K2.581.8%SourceNot directly comparable
FrontierMath v2 (Tiers 1-3)
GPT-6 Astra—Kimi K2.527.900%SourceNot directly comparable
Multilingual
Multimodal
ScreenSpot Pro
GPT-6 Astra92.7%SourceKimi K2.5—Not directly comparable
MMMU-Pro
GPT-6 Astra—Kimi K2.578.5%SourceNot directly comparable
Video-MME
GPT-6 Astra—Kimi K2.587.4%SourceNot directly comparable
MMVU
GPT-6 Astra—Kimi K2.580.4%SourceNot directly comparable
VideoMMMU
GPT-6 Astra—Kimi K2.586.6%SourceNot directly comparable
Instruction following
IFEval
GPT-6 Astra—Kimi K2.593.9%SourceNot directly comparable
Frequently asked questions
Which is better, GPT-6 Astra or Kimi K2.5?
GPT-6 Astra has the higher public score, 81.88 versus 58.81, 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 K2.5?
The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.
Which is better for agentic tasks, GPT-6 Astra or Kimi K2.5?
The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.
Which costs less, GPT-6 Astra or Kimi K2.5?
For the stated presets, chat costs $0.035 on GPT-6 Astra and $0.0021 on Kimi K2.5; repository review costs $0.65 and $0.039; the cache-heavy agent loop costs $0.9 and $0.162. Kimi K2.5 has no published cached-input rate, so cached tokens use its listed input rate.
Which has the larger context window, GPT-6 Astra or Kimi K2.5?
GPT-6 Astra has the larger documented context window: 1.05M, compared with 256K.
Related comparisons
Last updated September 3, 2026
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