Agentic
Not comparable- Claude Opus 5.5
- 82.7
- Supported · #1/156
- Toast 1
- Not ranked
- Basis
- BenchAlign lane · 11 vs 0 public rows
- Reading
- Not comparable
Claude Opus 5.5 vs Toast 1
Decision reading
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.
Updated September 22, 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
Share or export
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.
Long documents
Prompts that approach the documented context limit
Claude Opus 5.5
Claude Opus 5.5 has the larger documented context window.
Confidence: documented
Chat turn cost
1K fresh input + 500 output tokens
Toast 1
Toast 1 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
Toast 1
Toast 1 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Toast 1 is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Toast 1 is not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limited
Cache-heavy agent loop cost
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. Toast 1 does not fit this workload in one request.
Confidence: listed-rates
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.
76.0Claude Opus 5.5—Toast 1
Not comparable · BenchAlign
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.
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
48 Claude Opus 5.5 only
- Shared results
- 0
- Claude Opus 5.5 only
- 48
- Toast 1 only
- 0
- Like-for-like categories
- 0 / 8
Category results, on a stated basis
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.
Coding
Not comparable- Claude Opus 5.5
- 76.0
- Estimated · #4/159
- Toast 1
- Not ranked
- Basis
- BenchAlign lane · 9 vs 0 public rows
- Reading
- Not comparable
Reasoning
Not comparable- Claude Opus 5.5
- 78.5
- #4/19
- Toast 1
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Claude Opus 5.5
- 88.8
- #3/50
- Toast 1
- Not ranked
- Basis
- Provisional lane · 1 vs 0 weighted rows
- Reading
- Not comparable
Knowledge
Not comparable- Claude Opus 5.5
- 81.5
- Estimated · #3/187
- Toast 1
- Not ranked
- Basis
- BenchAlign lane · 17 vs 0 public rows
- Reading
- Not comparable
Multilingual
Not comparable- Claude Opus 5.5
- Not ranked
- Toast 1
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Claude Opus 5.5
- Not ranked
- Toast 1
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Claude Opus 5.5
- Not ranked
- Toast 1
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Claude Opus 5.5 | Toast 1 | Basis | Reading |
|---|---|---|---|---|
| Agentic | 82.7Supported · #1/156 | Not ranked | Not comparableBenchAlign lane · 11 vs 0 public rows | Not comparable |
| Coding | 76.0Estimated · #4/159 | Not ranked | Not comparableBenchAlign lane · 9 vs 0 public rows | Not comparable |
| Reasoning | 78.5#4/19 | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | 88.8#3/50 | Not ranked | Not comparableProvisional lane · 1 vs 0 weighted rows | Not comparable |
| Knowledge | 81.5Estimated · #3/187 | Not ranked | Not comparableBenchAlign lane · 17 vs 0 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) 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.
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.
A shared-evidence shape is not available.
BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.
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 Opus 5.5
- $0.014
- Fits in one request
- Toast 1
- $0.00066
- Fits in one request
Toast 1 has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- Claude Opus 5.5
- $0.26
- Fits in one request
- Toast 1
- $0.01716
- Fits in one request
Toast 1 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 Opus 5.5
- $0.32
- Fits in one request
- Toast 1
- $0.0204
- Does not fit in one request
Toast 1 does not fit this workload in one request.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationClaude Opus 5.5Toast 1
Context window
Maximum documented context; output-token limits may be lower.
Claude Opus 5.5
Toast 1
API model ID
Claude Opus 5.5
claude-opus-5-5
Anthropic Claude Opus 5.5 model documentationToast 1
Cached-input rate
A 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 documentationToast 1
$0.036 per 1M cached input tokens
Mixedbread pricingDocumented inputs
Claude Opus 5.5
Toast 1
Documented outputs
Claude Opus 5.5
Toast 1
Provider availability
Claude Opus 5.5
Generally Available · Claude API, Amazon Bedrock, Google Cloud, Microsoft Foundry, Claude Platform on AWS
Anthropic Claude Opus 5.5 model documentationToast 1
Generally Available · Mixedbread Chat Completions API
Mixedbread Toast 1 announcementReasoning profile
Claude Opus 5.5
Reasoning
Toast 1
Reasoning
Weight access
Claude Opus 5.5
Proprietary
Toast 1
Proprietary
License
Claude Opus 5.5
Proprietary
Toast 1
Proprietary
Release date
Claude Opus 5.5
2026-09-22
Toast 1
2026-08-13
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
- The public evidence has no benchmark result shared by both models, so it does not support a quality verdict.
- Workload cost
- Repository review: $0.26 vs $0.01716. Cache-heavy agent loop: $0.32 vs $0.0204.
- Context tradeoff
- Claude Opus 5.5 has the larger documented window (1M).
Run the same representative tasks against both endpoints before changing production traffic.
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 Opus 5.566.40%SourceToast 1—Not directly comparable
Terminal-Bench-Science 0.1
Claude Opus 5.558.7%SourceToast 1—Not directly comparable
AutomationBench
Claude Opus 5.540.0%SourceToast 1—Not directly comparable
HLE w/ tools
Claude Opus 5.567.7%SourceToast 1—Not directly comparable
OSWorld 2.0
Claude Opus 5.548.7%SourceToast 1—Not directly comparable
LAB all-pass (Harvey held-out)
Claude Opus 5.58.3%SourceToast 1—Not directly comparable
LAB criterion-pass (Harvey held-out)
Claude Opus 5.591.2%SourceToast 1—Not directly comparable
Toolathlon-Verified
Claude Opus 5.577.8%SourceToast 1—Not directly comparable
Toolathlon Verified Pass@3
Claude Opus 5.582.4%SourceToast 1—Not directly comparable
Toolathlon Verified Pass³
Claude Opus 5.572.2%SourceToast 1—Not directly comparable
Toolathlon Verified avg. turns
Claude Opus 5.526.9 turnsSourceToast 1—Not directly comparable
Coding
FrontierCode 1.1 Main
Claude Opus 5.554.4%SourceToast 1—Not directly comparable
cursorBench40
Claude Opus 5.557.8%SourceToast 1—Not directly comparable
SWE-bench Pro
Claude Opus 5.589.9%SourceToast 1—Not directly comparable
SWE Multilingual
Claude Opus 5.593.9%SourceToast 1—Not directly comparable
SWE Multimodal
Claude Opus 5.561.4%SourceToast 1—Not directly comparable
DeepSWE
Claude Opus 5.574.2%SourceToast 1—Not directly comparable
FrontierCode 1.1 Extended
Claude Opus 5.563.6%SourceToast 1—Not directly comparable
FrontierSWE v2
Claude Opus 5.562.3%SourceToast 1—Not directly comparable
ProgramBench
Claude Opus 5.591.2%SourceToast 1—Not directly comparable
Multimodal
Chartography (tools)
Claude Opus 5.589.0%SourceToast 1—Not directly comparable
Chartography (no tools)
Claude Opus 5.564.4%SourceToast 1—Not directly comparable
BenchCAD Vision2Code (no tools)
Claude Opus 5.50.730SourceToast 1—Not directly comparable
BenchCAD Vision2Code (tools)
Claude Opus 5.50.962SourceToast 1—Not directly comparable
Biomedical image analysis
Claude Opus 5.571.4%SourceToast 1—Not directly comparable
OfficeQA
Claude Opus 5.578.9%SourceToast 1—Not directly comparable
OfficeQA Pro
Claude Opus 5.567.7%SourceToast 1—Not directly comparable
Knowledge
HLE
Claude Opus 5.567.7%SourceToast 1—Not directly comparable
HLE w/o tools
Claude Opus 5.564.4%SourceToast 1—Not directly comparable
HealthBench (raw)
Claude Opus 5.568.1%SourceToast 1—Not directly comparable
HealthBench (length-adjusted)
Claude Opus 5.560.6%SourceToast 1—Not directly comparable
HealthBench Professional
Claude Opus 5.565.6%SourceToast 1—Not directly comparable
HealthBench Professional (raw)
Claude Opus 5.577.1%SourceToast 1—Not directly comparable
BioMysteryBench (human-solvable)
Claude Opus 5.589.3%SourceToast 1—Not directly comparable
BioMysteryBench (human-difficult)
Claude Opus 5.550.0%SourceToast 1—Not directly comparable
SpatialBench Verified
Claude Opus 5.572.0%SourceToast 1—Not directly comparable
SingleCellBench
Claude Opus 5.561.2%SourceToast 1—Not directly comparable
Morphology-to-molecule matching
Claude Opus 5.534.0%SourceToast 1—Not directly comparable
Medicinal chemistry
Claude Opus 5.563.5%SourceToast 1—Not directly comparable
Protein Design
Claude Opus 5.560.2%SourceToast 1—Not directly comparable
Protein Design library ranking
Claude Opus 5.556.0%SourceToast 1—Not directly comparable
De novo protein-binder design
Claude Opus 5.582.6%SourceToast 1—Not directly comparable
Protocols (troubleshooting)
Claude Opus 5.573.7%SourceToast 1—Not directly comparable
Protocols (understanding)
Claude Opus 5.569.0%SourceToast 1—Not directly comparable
Multilingual
Math
Questions
Which is better, Claude Opus 5.5 or Toast 1?
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.
Which is better for coding, Claude Opus 5.5 or Toast 1?
Toast 1 is not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, Claude Opus 5.5 or Toast 1?
Toast 1 is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, Claude Opus 5.5 or Toast 1?
For the stated presets, chat costs $0.014 on Claude Opus 5.5 and $0.00066 on Toast 1; repository review costs $0.26 and $0.01716; the cache-heavy agent loop costs $0.32 and $0.0204. Toast 1 does not fit this workload in one request.
Which has the larger context window, Claude Opus 5.5 or Toast 1?
Claude Opus 5.5 has the larger documented context window: 1M, compared with 131K.
Related comparisons
Last updated September 22, 2026
Watch Claude Opus 5.5 vs Toast 1
One weekly email when material rank, price, or benchmark evidence changes make this matchup worth revisiting.
Read a sample issueJoin 2,000+ readers.