Chat turn cost
1K fresh input + 500 output tokens
Pareto 26.9
Pareto 26.9 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Claude Sonnet 5.5 vs Pareto 26.9
Updated September 28, 2026. We do not rank this pair: at least one has no public score. 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
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Decision reading
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. 3 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
- Shared results
- 3
- Claude Sonnet 5.5 only
- 44
- Pareto 26.9 only
- 1
- Like-for-like categories
- 0 / 8
Estimated: Claude Sonnet 5.5How the comparison works
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.
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Pareto 26.9
Pareto 26.9 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Show secondary and unsupported calls
Repository review cost
50K fresh input + 3K output tokens
Claude Sonnet 5.5
Claude Sonnet 5.5 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-ratesCoding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Pareto 26.9 is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limitedAgentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Pareto 26.9 is not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limitedLong documents
Prompts that approach the documented context limit
Not enough matched evidence
A complete context comparison is not sourced.
Confidence: limited
Which one for a specific job
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.
79.6Claude Sonnet 5.5—Pareto 26.9
Not comparable · BenchAlign v5.7
The coding row is not comparable on the public lane: at least one model is not measured or not ranked there.
Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.
Same basis rules as the category table below
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
44 Claude Sonnet 5.5 only
3 Shared
1 Pareto 26.9 only
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.
HLE w/o toolsKnowledge
Normalized gap 7.9Claude Sonnet 5.5:56.9%Pareto 26.9:49%
Bars run 0–100 on each benchmark’s normalized display scale
Category results, on a stated basis
Each row shows the public-lane category score for both models: the BenchAlign v5.7 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.
Agentic
Not comparable- Claude Sonnet 5.5
- 66.1
- Supported · #10/111
- Pareto 26.9
- Not ranked
- Basis
- BenchAlign v5.7 lane · 11 vs 1 public rows
- Reading
- Not comparable
Coding
Not comparable- Claude Sonnet 5.5
- 79.6
- Estimated · #3/136
- Pareto 26.9
- Not ranked
- Basis
- BenchAlign v5.7 lane · 9 vs 1 public rows
- Reading
- Not comparable
Reasoning
Not comparable- Claude Sonnet 5.5
- 79.2
- #7/27
- Pareto 26.9
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Claude Sonnet 5.5
- 83.3
- Unranked · 7 rankable rows
- Pareto 26.9
- Not ranked
- Basis
- Provisional lane · 1 vs 1 weighted rows
- Reading
- Not comparable
Knowledge
Not comparable- Claude Sonnet 5.5
- 80.9
- Supported · #6/160
- Pareto 26.9
- Not ranked
- Basis
- BenchAlign v5.7 lane · 16 vs 1 public rows
- Reading
- Not comparable
Multilingual
Not comparable- Claude Sonnet 5.5
- Not ranked
- Pareto 26.9
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Claude Sonnet 5.5
- Not ranked
- Pareto 26.9
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Claude Sonnet 5.5
- Not ranked
- Pareto 26.9
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Claude Sonnet 5.5 | Pareto 26.9 | Basis | Reading |
|---|---|---|---|---|
| Agentic | 66.1Supported · #10/111 | Not ranked | Not comparableBenchAlign v5.7 lane · 11 vs 1 public rows | Not comparable |
| Coding | 79.6Estimated · #3/136 | Not ranked | Not comparableBenchAlign v5.7 lane · 9 vs 1 public rows | Not comparable |
| Reasoning | 79.2#7/27 | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | 83.3Unranked · 7 rankable rows | Not ranked | Not comparableProvisional lane · 1 vs 1 weighted rows | Not comparable |
| Knowledge | 80.9Supported · #6/160 | Not ranked | Not comparableBenchAlign v5.7 lane · 16 vs 1 public 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 v5.7) 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.
Supported evidence per lane · bars run 0–100Methodology
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
- Claude Sonnet 5.5
- $0.007
- Fits in one request
- Pareto 26.9
- $0.00625
- Fit state unavailable
Pareto 26.9 has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- Claude Sonnet 5.5
- $0.13
- Fits in one request
- Pareto 26.9
- $0.1475
- Fit state unavailable
Claude Sonnet 5.5 has the lower modeled cost
Costs use the listed standard API rates.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Claude Sonnet 5.5
- $0.18
- Fits in one request
- Pareto 26.9
- $0.175
- Fit state unavailable
Pareto 26.9 has the lower modeled cost
Costs use the listed standard API rates.
Cached input falls back to the list input rate only where a cached rate is unpublished
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationClaude Sonnet 5.5Pareto 26.9
Context window
Maximum documented context; output-token limits may be lower.
Claude Sonnet 5.5
Pareto 26.9
N/A
API model ID
Claude Sonnet 5.5
claude-sonnet-5-5
Anthropic Claude Sonnet 5.5 model documentationPareto 26.9
pareto
Unbiased pricingCached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Claude Sonnet 5.5
$0.2 per 1M cached input tokens
Claude API pricingPareto 26.9
$0.25 per 1M cached input tokens
Unbiased pricingDocumented inputs
Claude Sonnet 5.5
Pareto 26.9
Not sourced
Documented outputs
Claude Sonnet 5.5
Pareto 26.9
Not sourced
Provider availability
Claude Sonnet 5.5
Generally Available · Claude API, Amazon Bedrock, Google Cloud, Microsoft Foundry, Claude Platform on AWS
Anthropic Claude Sonnet 5.5 model documentationPareto 26.9
Not sourced
Reasoning profile
Claude Sonnet 5.5
Reasoning
Pareto 26.9
Reasoning
Weight access
Claude Sonnet 5.5
Proprietary
Pareto 26.9
Proprietary
License
Claude Sonnet 5.5
Proprietary
Pareto 26.9
Proprietary
Release date
Claude Sonnet 5.5
2026-09-28
Pareto 26.9
2026-09-17
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
- At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
- Workload cost
- Repository review: $0.13 vs $0.1475. Cache-heavy agent loop: $0.18 vs $0.175.
- Context tradeoff
- A complete documented context comparison is not available.
Run the same representative tasks against both endpoints before changing production traffic.
Questions
Which is better, Claude Sonnet 5.5 or Pareto 26.9?
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, Claude Sonnet 5.5 or Pareto 26.9?
Pareto 26.9 is not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, Claude Sonnet 5.5 or Pareto 26.9?
Pareto 26.9 is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, Claude Sonnet 5.5 or Pareto 26.9?
For the stated presets, chat costs $0.007 on Claude Sonnet 5.5 and $0.00625 on Pareto 26.9; repository review costs $0.13 and $0.1475; the cache-heavy agent loop costs $0.18 and $0.175. Costs use the listed standard API rates.
Which has the larger context window, Claude Sonnet 5.5 or Pareto 26.9?
A complete documented context-window comparison is not available.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence48 rows
Agentic
Terminal-Bench 4.0
Claude Sonnet 5.570.60%SourcePareto 26.951.00%SourceClaude Sonnet 5.5 leads this result
HLE w/ tools
Claude Sonnet 5.564.5%SourcePareto 26.9—Not directly comparable
DRACO
Claude Sonnet 5.587.0%SourcePareto 26.9—Not directly comparable
Terminal-Bench-Science 0.1
Claude Sonnet 5.559.9%SourcePareto 26.9—Not directly comparable
LAB all-pass (Harvey held-out)
Claude Sonnet 5.510.0%SourcePareto 26.9—Not directly comparable
LAB criterion-pass (Harvey held-out)
Claude Sonnet 5.593.1%SourcePareto 26.9—Not directly comparable
Toolathlon Verified Pass@3
Claude Sonnet 5.585.2%SourcePareto 26.9—Not directly comparable
Toolathlon Verified Pass³
Claude Sonnet 5.568.5%SourcePareto 26.9—Not directly comparable
Toolathlon Verified avg. turns
Claude Sonnet 5.531.6 turnsSourcePareto 26.9—Not directly comparable
AutomationBench (Zapier 1.0.6)
Claude Sonnet 5.544.7%SourcePareto 26.9—Not directly comparable
Toolathlon-Verified
Claude Sonnet 5.577.8%SourcePareto 26.9—Not directly comparable
Coding
FrontierCode 1.1 Main
Claude Sonnet 5.546.2%SourcePareto 26.9—Not directly comparable
cursorBench40
Claude Sonnet 5.555.5%SourcePareto 26.9—Not directly comparable
SWE-bench Pro
Claude Sonnet 5.581.3%SourcePareto 26.9—Not directly comparable
SWE Multilingual
Claude Sonnet 5.590.3%SourcePareto 26.9—Not directly comparable
SWE Multimodal
Claude Sonnet 5.554.3%SourcePareto 26.9—Not directly comparable
DeepSWE
Claude Sonnet 5.571.0%SourcePareto 26.974.0%SourcePareto 26.9 leads this result
FrontierCode 1.1 Extended
Claude Sonnet 5.559.1%SourcePareto 26.9—Not directly comparable
ProgramBench
Claude Sonnet 5.579.7%SourcePareto 26.9—Not directly comparable
FrontierSWE v2
Claude Sonnet 5.561.9%SourcePareto 26.9—Not directly comparable
Multimodal
Chartography (no tools)
Claude Sonnet 5.561.6%SourcePareto 26.9—Not directly comparable
Chartography (tools)
Claude Sonnet 5.590.2%SourcePareto 26.9—Not directly comparable
BenchCAD Vision2Code (no tools)
Claude Sonnet 5.50.747SourcePareto 26.9—Not directly comparable
BenchCAD Vision2Code (tools)
Claude Sonnet 5.50.963SourcePareto 26.9—Not directly comparable
Biomedical image analysis
Claude Sonnet 5.572.2%SourcePareto 26.9—Not directly comparable
OfficeQA
Claude Sonnet 5.576.9%SourcePareto 26.9—Not directly comparable
OfficeQA Pro
Claude Sonnet 5.565.6%SourcePareto 26.9—Not directly comparable
MMMU-Pro
Claude Sonnet 5.5—Pareto 26.978%SourceNot directly comparable
Knowledge
HealthBench (raw)
Claude Sonnet 5.569.4%SourcePareto 26.9—Not directly comparable
HealthBench (length-adjusted)
Claude Sonnet 5.565.4%SourcePareto 26.9—Not directly comparable
HealthBench Professional (raw)
Claude Sonnet 5.577.1%SourcePareto 26.9—Not directly comparable
HealthBench Professional
Claude Sonnet 5.569.2%SourcePareto 26.9—Not directly comparable
BioMysteryBench (human-solvable)
Claude Sonnet 5.589.2%SourcePareto 26.9—Not directly comparable
BioMysteryBench (human-difficult)
Claude Sonnet 5.544.7%SourcePareto 26.9—Not directly comparable
SpatialBench Verified
Claude Sonnet 5.572.5%SourcePareto 26.9—Not directly comparable
SingleCellBench
Claude Sonnet 5.559.1%SourcePareto 26.9—Not directly comparable
Protein Design
Claude Sonnet 5.551.0%SourcePareto 26.9—Not directly comparable
Morphology-to-molecule matching
Claude Sonnet 5.525.0%SourcePareto 26.9—Not directly comparable
Medicinal chemistry
Claude Sonnet 5.565.3%SourcePareto 26.9—Not directly comparable
Protein Design library ranking
Claude Sonnet 5.554.8%SourcePareto 26.9—Not directly comparable
De novo protein-binder design
Claude Sonnet 5.582.3%SourcePareto 26.9—Not directly comparable
Protocols (troubleshooting)
Claude Sonnet 5.567.3%SourcePareto 26.9—Not directly comparable
Protocols (understanding)
Claude Sonnet 5.566.6%SourcePareto 26.9—Not directly comparable
HLE w/o tools
Claude Sonnet 5.556.9%SourcePareto 26.949%SourceClaude Sonnet 5.5 leads this result
Multilingual
Math
48 public results · 3 shared
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Last updated September 28, 2026