Agentic
Like-for-like- Claude Sonnet 4.6
- 45.0
- Supported · #96/151
- Gemini 3.6 Flash
- 50.7
- Supported · #60/151
- Basis
- BenchAlign lane · 8 vs 2 public rows
- Reading
- Gemini 3.6 Flash leads · intervals overlap
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 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
Gemini 3.6 Flash has the higher public score estimate, 70.11 versus 64.21, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
6 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
Share or export
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.
Code generation, repair, and software-engineering tasks
Gemini 3.6 Flash
Gemini 3.6 Flash leads on the public coding lane, 58.9 to 52.4, with Supported evidence for both models, although the 90% intervals overlap.
Confidence: limited
Tool use, computer use, and multi-step task completion
Gemini 3.6 Flash
Gemini 3.6 Flash leads on the public agentic lane, 50.7 to 45, with Supported evidence for both models, although the 90% intervals overlap.
Confidence: limited
Prompts that approach the documented context limit
Gemini 3.6 Flash
Gemini 3.6 Flash has the larger documented context window.
Confidence: documented
1K fresh input + 500 output tokens
Gemini 3.6 Flash
Gemini 3.6 Flash 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
Gemini 3.6 Flash
Gemini 3.6 Flash 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
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. Claude Sonnet 4.6 does not fit this workload in one request. Claude Sonnet 4.6 has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
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.
| Category | Claude Sonnet 4.6 | Gemini 3.6 Flash | Basis | Reading |
|---|---|---|---|---|
| Agentic | 45.0Supported · #96/151 | 50.7Supported · #60/151 | Like-for-likeBenchAlign lane · 8 vs 2 public rows | Gemini 3.6 Flash leads · intervals overlap |
| Coding | 52.4Supported · #55/183 | 58.9Supported · #30/183 | Like-for-likeBenchAlign lane · 8 vs 4 public rows | Gemini 3.6 Flash leads · intervals overlap |
| Knowledge | 56.7Supported · #51/181 | 68.6Supported · #18/181 | Like-for-likeBenchAlign lane · 6 vs 2 public rows | Gemini 3.6 Flash leads · intervals overlap |
| Reasoning | 65.8Unranked · 2 rankable rows | 77.8Unranked · 2 rankable rows | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | 49.0Unranked · 2 rankable rows | 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 | 53.9#33/48 | 82.3Unranked · 1 rankable row | Not comparableProvisional lane · 1 vs 0 weighted rows | Not comparable |
| Instruction following | 47.9#84/120 | 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, 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.
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.
OSWorld-Verified
Agentic
LiveCodeBench (Vals)
Coding
MMLU-Pro (Vals)
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
Gemini 3.6 Flash has the lower modeled cost
Costs use the listed standard API rates.
50K fresh input + 3K output tokens
Gemini 3.6 Flash has the lower modeled cost
Costs use the listed standard API rates.
200K cached + 20K fresh input + 10K output tokens
Claude Sonnet 4.6 does not fit this workload in one request. Claude Sonnet 4.6 has no published cached-input rate, so cached tokens use its listed input rate.
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.
Claude Sonnet 4.6
200K
Gemini 3.6 Flash
Claude Sonnet 4.6
Not sourced
Gemini 3.6 Flash
gemini-3.6-flash
Google Gemini 3.6 Flash model documentationA missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Claude Sonnet 4.6
Not published
Gemini 3.6 Flash
$0.15 per 1M cached input tokens
Google Gemini API pricingClaude Sonnet 4.6
Not sourced
Gemini 3.6 Flash
text, image, video, audio, pdf
Google Gemini 3.6 Flash model documentationClaude Sonnet 4.6
Not sourced
Gemini 3.6 Flash
Claude Sonnet 4.6
Not sourced
Gemini 3.6 Flash
Generally Available · Gemini API, Google AI Studio
Google latest Gemini model guideClaude Sonnet 4.6
Non-Reasoning
Gemini 3.6 Flash
Reasoning
Claude Sonnet 4.6
Proprietary
Gemini 3.6 Flash
Proprietary
Claude Sonnet 4.6
Proprietary
Gemini 3.6 Flash
Proprietary
Claude Sonnet 4.6
2026-02-01
Gemini 3.6 Flash
2026-07-21
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.
Terminal-Bench 2.0
Not directly comparable
OSWorld-Verified
Gemini 3.6 Flash leads this result
Claw-Eval
Not directly comparable
CyberGym
Not directly comparable
Gert Labs
Not directly comparable
OSWorld 2.0
Not directly comparable
JobBench
Not directly comparable
Terminal-Bench 2.1 (Vals)
Gemini 3.6 Flash leads this result
SWE-bench Verified
Not directly comparable
SWE-Rebench
Not directly comparable
React Native Evals
Not directly comparable
Vibe Code Bench
Not directly comparable
cursorBench31
Not directly comparable
FrontierCode 1.1 Main
Not directly comparable
LiveCodeBench (Vals)
Gemini 3.6 Flash leads this result
SWE-bench (Vals)
Gemini 3.6 Flash leads this result
deepSwe
Not directly comparable
cursorBench32
Not directly comparable
GPQA
Not directly comparable
SuperGPQA
Not directly comparable
MMLU-Pro
Not directly comparable
HLE
Not directly comparable
GPQA Diamond (Vals)
Gemini 3.6 Flash leads this result
MMLU-Pro (Vals)
Gemini 3.6 Flash leads this result
CharXiv
Not directly comparable
Gemini 3.6 Flash has the higher public score estimate, 70.11 versus 64.21, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.
Gemini 3.6 Flash leads the public coding lane, 58.9 to 52.4, with Supported evidence for both models, although the 90% intervals overlap.
Gemini 3.6 Flash leads the public agentic tasks lane, 50.7 to 45, with Supported evidence for both models, although the 90% intervals overlap.
For the stated presets, chat costs $0.0105 on Claude Sonnet 4.6 and $0.00525 on Gemini 3.6 Flash; repository review costs $0.195 and $0.0975; the cache-heavy agent loop costs $0.81 and $0.135. Claude Sonnet 4.6 does not fit this workload in one request. Claude Sonnet 4.6 has no published cached-input rate, so cached tokens use its listed input rate.
Gemini 3.6 Flash has the larger documented context window: 1M, compared with 200K.
Last updated September 4, 2026
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