Knowledge
Directional only- GPT-6 Astra
- 96.0
- Kimi K3
- 61.0
- Weighted basis
- 1 vs 2 rows
- Reading
- Directional only
Five or fewer confirmed AI changes, with original sources, on mornings when something changed.A free source-linked morning brief.
See the free Radar BriefUpdated 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 estimate, 81.88 versus 79.65, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
3 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.
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.
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
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
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
Code generation, repair, and software-engineering tasks
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
Tool use, computer use, and multi-step task completion
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documented
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
1 category uses different evidence sets. Those rows remain visible for coverage context but do not name a winner.
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.
| Category | GPT-6 Astra | Kimi K3 | Weighted basis | Reading |
|---|---|---|---|---|
| Knowledge | 96.0 | 61.0 | Directional only1 vs 2 rows | Directional only |
| Agentic | Not measured | 89.5 | Not comparable0 vs 2 rows | Not comparable |
| Coding | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Reasoning | 95.0 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Math | 97.6 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Multilingual | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multimodal | Not measured | 78.5 | Not comparable0 vs 3 rows | Not comparable |
| Instruction following | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
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.
GPQA
Knowledge
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.
1K fresh input + 500 output tokens
Kimi K3 has the lower modeled cost
Costs use the listed standard API rates.
50K fresh input + 3K output tokens
Kimi K3 has the lower modeled cost
Costs use the listed standard API rates.
200K cached + 20K fresh input + 10K output tokens
Kimi K3 has the lower modeled cost
Costs use the listed standard API rates.
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
Maximum documented context; output-token limits may be lower.
GPT-6 Astra
Kimi K3
1.05M
GPT-6 Astra
gpt-6-astra
OpenAI GPT-6 Astra model documentationKimi K3
Not sourced
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 K3
$0.3 per 1M cached input tokens
GPT-6 Astra
text, image
OpenAI GPT-6 Astra model documentationKimi K3
Not sourced
GPT-6 Astra
Kimi K3
Not sourced
GPT-6 Astra
Limited Availability · OpenAI Responses API, ChatGPT Plus, Pro, Business, and Enterprise
OpenAI GPT-6 Astra model documentationKimi K3
Not sourced
GPT-6 Astra
Reasoning
Kimi K3
Reasoning
GPT-6 Astra
Proprietary
Kimi K3
Pending
GPT-6 Astra
Proprietary
Kimi K3
Pending
GPT-6 Astra
2026-09-03
Kimi K3
2026-07-16
Run the same representative tasks against both endpoints before changing production traffic.
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
OSWorld 2.0
Not directly comparable
Terminal-Bench 4.0
Not directly comparable
Terminal-Bench-Science 0.1
Not directly comparable
ExploitGym
Not directly comparable
Agents' Last Exam
Not directly comparable
Terminal-Bench 2.0
Not directly comparable
BrowseComp
Not directly comparable
DeepSearchQA
Not directly comparable
Toolathlon-Verified
Not directly comparable
MCP Atlas
Not directly comparable
AutomationBench
Not directly comparable
JobBench
Not directly comparable
APEX-Agents
Not directly comparable
SpreadsheetBench 2
Not directly comparable
DECK-Bench
Not directly comparable
deepSwe
GPT-6 Astra leads this result
cursorBench32
Not directly comparable
FrontierSWE
Not directly comparable
ProgramBench
Not directly comparable
Kimi Code Bench v2
Not directly comparable
sweMarathon
Not directly comparable
PostTrain Bench
Not directly comparable
MLS-Bench Lite
Not directly comparable
VulcanBench v3
Not directly comparable
OpenHarmony Bench
Not directly comparable
FrontierSWE v2
Not directly comparable
GPQA
GPT-6 Astra leads this result
GPQA-D
GPT-6 Astra leads this result
HealthBench Professional
Not directly comparable
HealthBench Hard
Not directly comparable
HLE
Not directly comparable
HLE w/o tools
Not directly comparable
FrontierMath v2 (Tier 4)
Not directly comparable
ScreenSpot Pro
Not directly comparable
OfficeQA Pro
Not directly comparable
MMMU-Pro
Not directly comparable
MMMU-Pro w/ Python
Not directly comparable
CharXiv w/o tools
Not directly comparable
CharXiv
Not directly comparable
MathVision
Not directly comparable
MathVision w/ Python
Not directly comparable
BabyVision w/ Python
Not directly comparable
ZeroBench
Not directly comparable
ZeroBench w/ Python
Not directly comparable
WorldVQA ForceAnswer
Not directly comparable
OmniDocBench
Not directly comparable
PerceptionBench
Not directly comparable
GPT-6 Astra has the higher public score estimate, 81.88 versus 79.65, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.
The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.
The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.
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.
Both models list the same context window, 1.05M.
Last updated September 3, 2026
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