Chat turn cost
1K fresh input + 500 output tokens
Gemini 3.1 Flash-Lite
Gemini 3.1 Flash-Lite has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Updated September 23, 2026. Rank says Claude Opus 5.5 is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.
Both of these models will change. Get the price, version and retirement notices for the pair, each with its source. Follow model changes
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. Use the documented cost, context, and runtime rows instead. 0 results are shared. Category rows resting on Estimated evidence or 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
Gemini 3.1 Flash-Lite
Gemini 3.1 Flash-Lite has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
200K cached + 20K fresh input + 10K output tokens
Gemini 3.1 Flash-Lite
Gemini 3.1 Flash-Lite has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
50K fresh input + 3K output tokens
Gemini 3.1 Flash-Lite
Gemini 3.1 Flash-Lite has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Gemini 3.1 Flash-Lite is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Gemini 3.1 Flash-Lite is scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
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.
The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.
Directional only · BenchAlign v5.6
Claude Opus 5.5 scores higher, but at least one score rests on Estimated evidence or a different benchmark set. Directional only, no winner.
Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
3 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.
Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.
A shared-evidence shape is not available.
BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.
Each row shows the public-lane category score for both models: the BenchAlign v5.6 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 5.5 | Gemini 3.1 Flash-Lite | Basis | Reading |
|---|---|---|---|---|
| Agentic | 88.8Supported · #1/105 | 27.5Estimated · #73/105 | Directional onlyBenchAlign v5.6 lane · 11 vs 2 public rows | Directional only |
| Coding | 87.1Supported · #1/135 | 28.4Estimated · #100/135 | Directional onlyBenchAlign v5.6 lane · 9 vs 3 public rows | Directional only |
| Knowledge | 90.0Supported · #1/160 | 44.0Estimated · #73/160 | Directional onlyBenchAlign v5.6 lane · 16 vs 2 public rows | Directional only |
| Reasoning | 78.5#4/18 | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | 88.8#3/50 | 37.4Unranked · 1 rankable row | Not comparableProvisional lane · 1 vs 1 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 | 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 v5.6) 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.
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 3.1 Flash-Lite has the lower modeled cost
Costs use the listed standard API rates.
50K fresh input + 3K output tokens
Gemini 3.1 Flash-Lite has the lower modeled cost
Costs use the listed standard API rates.
200K cached + 20K fresh input + 10K output tokens
Gemini 3.1 Flash-Lite 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.
Claude Opus 5.5
Gemini 3.1 Flash-Lite
Claude Opus 5.5
claude-opus-5-5
Anthropic Claude Opus 5.5 model documentationGemini 3.1 Flash-Lite
gemini-3.1-flash-lite
Google Gemini API pricingA missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Claude Opus 5.5
$0.2 per 1M cached input tokens
Claude Opus 5.5 model documentationGemini 3.1 Flash-Lite
$0.025 per 1M cached input tokens
Google Gemini API pricingClaude Opus 5.5
Gemini 3.1 Flash-Lite
Not sourced
Claude Opus 5.5
Gemini 3.1 Flash-Lite
Not sourced
Claude Opus 5.5
Generally Available · Claude API, Amazon Bedrock, Google Cloud, Microsoft Foundry, Claude Platform on AWS
Anthropic Claude Opus 5.5 model documentationGemini 3.1 Flash-Lite
Not sourced
Claude Opus 5.5
Reasoning
Gemini 3.1 Flash-Lite
Non-Reasoning
Claude Opus 5.5
Proprietary
Gemini 3.1 Flash-Lite
Proprietary
Claude Opus 5.5
Proprietary
Gemini 3.1 Flash-Lite
Proprietary
Claude Opus 5.5
2026-09-22
Gemini 3.1 Flash-Lite
2026-03-03
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. The page therefore keeps the decision tied to the specific documented workload.
Claude Opus 5.5 scores higher for coding on the public lane, 87.1 to 28.4. Gemini 3.1 Flash-Lite is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like. BenchLM does not name a winner for coding from a directional reading; read the shared benchmark rows directly and test the models on the same task set.
Claude Opus 5.5 scores higher for agentic tasks on the public lane, 88.8 to 27.5. Gemini 3.1 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 $0.014 on Claude Opus 5.5 and $0.001 on Gemini 3.1 Flash-Lite; repository review costs $0.26 and $0.017; the cache-heavy agent loop costs $0.32 and $0.025. Costs use the listed standard API rates.
Both models list the same context window, 1M.
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Terminal-Bench 4.0
Not directly comparable
Terminal-Bench-Science 0.1
Not directly comparable
AutomationBench
Not directly comparable
HLE w/ tools
Not directly comparable
OSWorld 2.0
Not directly comparable
LAB all-pass (Harvey held-out)
Not directly comparable
LAB criterion-pass (Harvey held-out)
Not directly comparable
Toolathlon-Verified
Not directly comparable
Toolathlon Verified Pass@3
Not directly comparable
Toolathlon Verified Pass³
Not directly comparable
Toolathlon Verified avg. turns
Not directly comparable
Gert Labs
Not directly comparable
Terminal-Bench 2.1 (Vals)
Not directly comparable
FrontierCode 1.1 Main
Not directly comparable
cursorBench40
Not directly comparable
SWE-bench Pro
Not directly comparable
SWE Multilingual
Not directly comparable
SWE Multimodal
Not directly comparable
DeepSWE
Not directly comparable
FrontierCode 1.1 Extended
Not directly comparable
FrontierSWE v2
Not directly comparable
ProgramBench
Not directly comparable
Vibe Code Bench
Not directly comparable
LiveCodeBench (Vals)
Not directly comparable
SWE-bench (Vals)
Not directly comparable
Chartography (tools)
Not directly comparable
Chartography (no tools)
Not directly comparable
BenchCAD Vision2Code (no tools)
Not directly comparable
BenchCAD Vision2Code (tools)
Not directly comparable
Biomedical image analysis
Not directly comparable
OfficeQA
Not directly comparable
OfficeQA Pro
Not directly comparable
CharXiv
Not directly comparable
HLE w/o tools
Not directly comparable
HealthBench (raw)
Not directly comparable
HealthBench (length-adjusted)
Not directly comparable
HealthBench Professional
Not directly comparable
HealthBench Professional (raw)
Not directly comparable
BioMysteryBench (human-solvable)
Not directly comparable
BioMysteryBench (human-difficult)
Not directly comparable
SpatialBench Verified
Not directly comparable
SingleCellBench
Not directly comparable
Morphology-to-molecule matching
Not directly comparable
Medicinal chemistry
Not directly comparable
Protein Design
Not directly comparable
Protein Design library ranking
Not directly comparable
De novo protein-binder design
Not directly comparable
Protocols (troubleshooting)
Not directly comparable
Protocols (understanding)
Not directly comparable
GPQA Diamond (Vals)
Not directly comparable
MMLU-Pro (Vals)
Not directly comparable
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Last updated September 23, 2026