Coding
Like-for-like- Claude Opus 4.7
- 62.7
- Supported · #15/183
- Gemini 3.5 Flash-Lite
- 43.6
- Supported · #121/183
- Basis
- BenchAlign lane · 5 vs 4 public rows
- Reading
- Claude Opus 4.7 leads
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
Claude Opus 4.7 has the higher public score estimate, 70.22 versus 60.5, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
5 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
Claude Opus 4.7
Claude Opus 4.7 leads on the public coding lane, 62.7 to 43.6, with Supported evidence for both models and non-overlapping 90% intervals.
Confidence: stronger
1K fresh input + 500 output tokens
Gemini 3.5 Flash-Lite
Gemini 3.5 Flash-Lite 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
Gemini 3.5 Flash-Lite
Gemini 3.5 Flash-Lite has the lower estimated token cost for this stated workload. Claude Opus 4.7 has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback
50K fresh input + 3K output tokens
Gemini 3.5 Flash-Lite
Gemini 3.5 Flash-Lite has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Gemini 3.5 Flash-Lite is scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.
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.
2 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.
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 Opus 4.7 | Gemini 3.5 Flash-Lite | Basis | Reading |
|---|---|---|---|---|
| Coding | 62.7Supported · #15/183 | 43.6Supported · #121/183 | Like-for-likeBenchAlign lane · 5 vs 4 public rows | Claude Opus 4.7 leads |
| Agentic | 58.5Supported · #33/151 | 43.4Estimated · #104/151 | Directional onlyBenchAlign lane · 4 vs 3 public rows | Directional only |
| Knowledge | 64.9Estimated · #26/181 | 53.0Supported · #71/181 | Directional onlyBenchAlign lane · 2 vs 2 public rows | Directional only |
| Reasoning | Not ranked | 60.8Unranked · 3 rankable rows | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
| Math | 60.8Unranked · 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 | Not ranked | 76.1#16/48 | 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 |
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.
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 3.5 Flash-Lite has the lower modeled cost
Costs use the listed standard API rates.
50K fresh input + 3K output tokens
Gemini 3.5 Flash-Lite has the lower modeled cost
Costs use the listed standard API rates.
200K cached + 20K fresh input + 10K output tokens
Gemini 3.5 Flash-Lite has the lower modeled cost
Claude Opus 4.7 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 Opus 4.7
Gemini 3.5 Flash-Lite
Claude Opus 4.7
claude-opus-4-7
Anthropic model ID documentationGemini 3.5 Flash-Lite
gemini-3.5-flash-lite
Google Gemini 3.5 Flash-Lite model documentationA missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Claude Opus 4.7
Not published
Gemini 3.5 Flash-Lite
$0.03 per 1M cached input tokens
Google Gemini API pricingClaude Opus 4.7
text, image
Anthropic model overviewGemini 3.5 Flash-Lite
text, image, video, audio, pdf
Google Gemini 3.5 Flash-Lite model documentationClaude Opus 4.7
Gemini 3.5 Flash-Lite
Claude Opus 4.7
Generally Available · Claude API
Anthropic model overviewGemini 3.5 Flash-Lite
Generally Available · Gemini API, Google AI Studio
Google latest Gemini model guideClaude Opus 4.7
Non-Reasoning
Gemini 3.5 Flash-Lite
Reasoning
Claude Opus 4.7
Proprietary
Gemini 3.5 Flash-Lite
Proprietary
Claude Opus 4.7
Proprietary
Gemini 3.5 Flash-Lite
Proprietary
Claude Opus 4.7
2026-04-16
Gemini 3.5 Flash-Lite
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.
Gert Labs
Not directly comparable
ResearchClawBench
Not directly comparable
OSWorld 2.0
Not directly comparable
Terminal-Bench 2.1 (Vals)
Claude Opus 4.7 leads this result
Terminal-Bench 2.0
Not directly comparable
OSWorld-Verified
Not directly comparable
Vibe Code Bench
Not directly comparable
React Native Evals
Not directly comparable
FrontierCode 1.1 Main
Not directly comparable
LiveCodeBench (Vals)
Claude Opus 4.7 leads this result
SWE-bench (Vals)
Claude Opus 4.7 leads this result
Terminal-Bench 2.0
Not directly comparable
SWE-bench Pro
Not directly comparable
MRCRv2
Not directly comparable
Claude Opus 4.7 has the higher public score estimate, 70.22 versus 60.5, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.
Claude Opus 4.7 leads the public coding lane, 62.7 to 43.6, with Supported evidence for both models and non-overlapping 90% intervals.
Claude Opus 4.7 scores higher for agentic tasks on the public lane, 58.5 to 43.4. Gemini 3.5 Flash-Lite is scored on Estimated evidence for agentic tasks, so the reading is directional rather than like-for-like. BenchLM does not name a winner for agentic tasks from a directional reading; read the shared benchmark rows directly and test the models on the same task set.
For the stated presets, chat costs $0.0175 on Claude Opus 4.7 and $0.00155 on Gemini 3.5 Flash-Lite; repository review costs $0.325 and $0.0225; the cache-heavy agent loop costs $1.35 and $0.037. Claude Opus 4.7 has no published cached-input rate, so cached tokens use its listed input rate.
Both models list the same context window, 1M.
Last updated September 4, 2026
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