Agentic
Like-for-like- Claude Haiku 4.5
- 29.1
- Supported · #148/157
- Claude Opus 5.5
- 82.9
- Supported · #1/157
- Basis
- BenchAlign lane · 2 vs 11 public rows
- Reading
- Claude Opus 5.5 leads
Claude Haiku 4.5 vs Claude Opus 5.5
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. 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
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.
Coding work
Code generation, repair, and software-engineering tasks
Claude Opus 5.5
Claude Opus 5.5 leads on the public coding lane, 80.1 to 27.7, with Supported evidence for both models and non-overlapping 90% intervals.
Confidence: stronger
Agentic work
Tool use, computer use, and multi-step task completion
Claude Opus 5.5
Claude Opus 5.5 leads on the public agentic lane, 82.9 to 29.1, with Supported evidence for both models and non-overlapping 90% intervals.
Confidence: stronger
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
Show secondary and unsupported calls
Chat turn cost
1K fresh input + 500 output tokens
Claude Haiku 4.5
Claude Haiku 4.5 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Repository review cost
50K fresh input + 3K output tokens
Claude Haiku 4.5
Claude Haiku 4.5 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
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. Claude Haiku 4.5 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.
27.7Claude Haiku 4.580.1Claude Opus 5.5
Like-for-like · BenchAlign
Claude Opus 5.5 leads the like-for-like coding row.
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.
10 Claude Haiku 4.5 only
47 Claude Opus 5.5 only
- Shared results
- 0
- Claude Haiku 4.5 only
- 10
- Claude Opus 5.5 only
- 47
- Like-for-like categories
- 2 / 8
1 category rests on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.
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
Like-for-like- Claude Haiku 4.5
- 27.7
- Supported · #152/159
- Claude Opus 5.5
- 80.1
- Supported · #2/159
- Basis
- BenchAlign lane · 4 vs 9 public rows
- Reading
- Claude Opus 5.5 leads
Knowledge
Directional only- Claude Haiku 4.5
- 43.9
- Estimated · #125/189
- Claude Opus 5.5
- 81.8
- Estimated · #4/189
- Basis
- BenchAlign lane · 2 vs 16 public rows
- Reading
- Directional only
Reasoning
Not comparable- Claude Haiku 4.5
- Not ranked
- Claude Opus 5.5
- 78.5
- #4/17
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Claude Haiku 4.5
- Not ranked
- Claude Opus 5.5
- 88.8
- #3/50
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Claude Haiku 4.5
- Not ranked
- Claude Opus 5.5
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Claude Haiku 4.5
- Not ranked
- Claude Opus 5.5
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Claude Haiku 4.5
- 28.8
- Unranked · 2 rankable rows
- Claude Opus 5.5
- Not ranked
- Basis
- Provisional lane · 2 vs 0 weighted rows
- Reading
- Not comparable
| Category | Claude Haiku 4.5 | Claude Opus 5.5 | Basis | Reading |
|---|---|---|---|---|
| Agentic | 29.1Supported · #148/157 | 82.9Supported · #1/157 | Like-for-likeBenchAlign lane · 2 vs 11 public rows | Claude Opus 5.5 leads |
| Coding | 27.7Supported · #152/159 | 80.1Supported · #2/159 | Like-for-likeBenchAlign lane · 4 vs 9 public rows | Claude Opus 5.5 leads |
| Knowledge | 43.9Estimated · #125/189 | 81.8Estimated · #4/189 | Directional onlyBenchAlign lane · 2 vs 16 public rows | Directional only |
| Reasoning | Not ranked | 78.5#4/17 | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | Not ranked | 88.8#3/50 | Not comparableProvisional lane · 0 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 | 28.8Unranked · 2 rankable rows | Not ranked | Not comparableProvisional lane · 2 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 Haiku 4.5
- $0.0035
- Fits in one request
- Claude Opus 5.5
- $0.014
- Fits in one request
Claude Haiku 4.5 has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- Claude Haiku 4.5
- $0.065
- Fits in one request
- Claude Opus 5.5
- $0.26
- Fits in one request
Claude Haiku 4.5 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 Haiku 4.5
- $0.09
- Does not fit in one request
- Claude Opus 5.5
- $0.32
- Fits in one request
Claude Haiku 4.5 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 Haiku 4.5Claude Opus 5.5
Context window
Maximum documented context; output-token limits may be lower.
Claude Haiku 4.5
Claude Opus 5.5
API model ID
Claude Haiku 4.5
claude-haiku-4-5-20251001
Claude API pricingClaude Opus 5.5
claude-opus-5-5
Anthropic Claude Opus 5.5 model documentationCached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Claude Haiku 4.5
$0.1 per 1M cached input tokens
Claude API pricingClaude Opus 5.5
$0.2 per 1M cached input tokens
Claude Opus 5.5 model documentationDocumented inputs
Claude Haiku 4.5
Not sourced
Claude Opus 5.5
Documented outputs
Claude Haiku 4.5
Not sourced
Claude Opus 5.5
Provider availability
Claude Haiku 4.5
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 documentationReasoning profile
Claude Haiku 4.5
Non-Reasoning
Claude Opus 5.5
Reasoning
Weight access
Claude Haiku 4.5
Proprietary
Claude Opus 5.5
Proprietary
License
Claude Haiku 4.5
Proprietary
Claude Opus 5.5
Proprietary
Release date
Claude Haiku 4.5
2025-10-15
Claude Opus 5.5
2026-09-22
If you already use one of these models
- Deployment change
- Both entries list Anthropic as the provider. Confirm endpoint, model ID, limits, and feature support before switching.
- 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: $0.065 vs $0.26. Cache-heavy agent loop: $0.09 vs $0.32.
- 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 evidence57 rows
Agentic
JobBench
Claude Haiku 4.516.0%SourceClaude Opus 5.5—Not directly comparable
Terminal-Bench 2.1 (Vals)
Claude Haiku 4.543.8%SourceClaude Opus 5.5—Not directly comparable
Terminal-Bench 4.0
Claude Haiku 4.5—Claude Opus 5.566.40%SourceNot directly comparable
Terminal-Bench-Science 0.1
Claude Haiku 4.5—Claude Opus 5.558.7%SourceNot directly comparable
AutomationBench
Claude Haiku 4.5—Claude Opus 5.540.0%SourceNot directly comparable
HLE w/ tools
Claude Haiku 4.5—Claude Opus 5.567.7%SourceNot directly comparable
OSWorld 2.0
Claude Haiku 4.5—Claude Opus 5.548.7%SourceNot directly comparable
LAB all-pass (Harvey held-out)
Claude Haiku 4.5—Claude Opus 5.58.3%SourceNot directly comparable
LAB criterion-pass (Harvey held-out)
Claude Haiku 4.5—Claude Opus 5.591.2%SourceNot directly comparable
Toolathlon-Verified
Claude Haiku 4.5—Claude Opus 5.577.8%SourceNot directly comparable
Toolathlon Verified Pass@3
Claude Haiku 4.5—Claude Opus 5.582.4%SourceNot directly comparable
Toolathlon Verified Pass³
Claude Haiku 4.5—Claude Opus 5.572.2%SourceNot directly comparable
Toolathlon Verified avg. turns
Claude Haiku 4.5—Claude Opus 5.526.9 turnsSourceNot directly comparable
Coding
SWE-bench Verified
Claude Haiku 4.573.3%SourceClaude Opus 5.5—Not directly comparable
VulcanBench v3
Claude Haiku 4.576.2%SourceClaude Opus 5.5—Not directly comparable
LiveCodeBench (Vals)
Claude Haiku 4.541.2%SourceClaude Opus 5.5—Not directly comparable
SWE-bench (Vals)
Claude Haiku 4.566.6%SourceClaude Opus 5.5—Not directly comparable
FrontierCode 1.1 Main
Claude Haiku 4.5—Claude Opus 5.554.4%SourceNot directly comparable
cursorBench40
Claude Haiku 4.5—Claude Opus 5.557.8%SourceNot directly comparable
SWE-bench Pro
Claude Haiku 4.5—Claude Opus 5.589.9%SourceNot directly comparable
SWE Multilingual
Claude Haiku 4.5—Claude Opus 5.593.9%SourceNot directly comparable
SWE Multimodal
Claude Haiku 4.5—Claude Opus 5.561.4%SourceNot directly comparable
DeepSWE
Claude Haiku 4.5—Claude Opus 5.574.2%SourceNot directly comparable
FrontierCode 1.1 Extended
Claude Haiku 4.5—Claude Opus 5.563.6%SourceNot directly comparable
FrontierSWE v2
Claude Haiku 4.5—Claude Opus 5.562.3%SourceNot directly comparable
ProgramBench
Claude Haiku 4.5—Claude Opus 5.591.2%SourceNot directly comparable
Multimodal
Chartography (tools)
Claude Haiku 4.5—Claude Opus 5.589.0%SourceNot directly comparable
Chartography (no tools)
Claude Haiku 4.5—Claude Opus 5.564.4%SourceNot directly comparable
BenchCAD Vision2Code (no tools)
Claude Haiku 4.5—Claude Opus 5.50.730SourceNot directly comparable
BenchCAD Vision2Code (tools)
Claude Haiku 4.5—Claude Opus 5.50.962SourceNot directly comparable
Biomedical image analysis
Claude Haiku 4.5—Claude Opus 5.571.4%SourceNot directly comparable
OfficeQA
Claude Haiku 4.5—Claude Opus 5.578.9%SourceNot directly comparable
OfficeQA Pro
Claude Haiku 4.5—Claude Opus 5.567.7%SourceNot directly comparable
Knowledge
GPQA Diamond (Vals)
Claude Haiku 4.572.2%SourceClaude Opus 5.5—Not directly comparable
MMLU-Pro (Vals)
Claude Haiku 4.578.7%SourceClaude Opus 5.5—Not directly comparable
HLE w/o tools
Claude Haiku 4.5—Claude Opus 5.564.4%SourceNot directly comparable
HealthBench (raw)
Claude Haiku 4.5—Claude Opus 5.568.1%SourceNot directly comparable
HealthBench (length-adjusted)
Claude Haiku 4.5—Claude Opus 5.560.6%SourceNot directly comparable
HealthBench Professional
Claude Haiku 4.5—Claude Opus 5.565.6%SourceNot directly comparable
HealthBench Professional (raw)
Claude Haiku 4.5—Claude Opus 5.577.1%SourceNot directly comparable
BioMysteryBench (human-solvable)
Claude Haiku 4.5—Claude Opus 5.589.3%SourceNot directly comparable
BioMysteryBench (human-difficult)
Claude Haiku 4.5—Claude Opus 5.550.0%SourceNot directly comparable
SpatialBench Verified
Claude Haiku 4.5—Claude Opus 5.572.0%SourceNot directly comparable
SingleCellBench
Claude Haiku 4.5—Claude Opus 5.561.2%SourceNot directly comparable
Morphology-to-molecule matching
Claude Haiku 4.5—Claude Opus 5.534.0%SourceNot directly comparable
Medicinal chemistry
Claude Haiku 4.5—Claude Opus 5.563.5%SourceNot directly comparable
Protein Design
Claude Haiku 4.5—Claude Opus 5.560.2%SourceNot directly comparable
Protein Design library ranking
Claude Haiku 4.5—Claude Opus 5.556.0%SourceNot directly comparable
De novo protein-binder design
Claude Haiku 4.5—Claude Opus 5.582.6%SourceNot directly comparable
Protocols (troubleshooting)
Claude Haiku 4.5—Claude Opus 5.573.7%SourceNot directly comparable
Protocols (understanding)
Claude Haiku 4.5—Claude Opus 5.569.0%SourceNot directly comparable
Multilingual
Math
FrontierMath v2 (Tiers 1-3)
Claude Haiku 4.55.903%SourceClaude Opus 5.5—Not directly comparable
FrontierMath v2 (Tier 4)
Claude Haiku 4.52.083%SourceClaude Opus 5.5—Not directly comparable
ArXivMath Aug. 2026 (no tools)
Claude Haiku 4.5—Claude Opus 5.591.2%SourceNot directly comparable
ArXivMath Aug. 2026 (tools)
Claude Haiku 4.5—Claude Opus 5.596.9%SourceNot directly comparable
Questions
Which is better, Claude Haiku 4.5 or Claude Opus 5.5?
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 Haiku 4.5 or Claude Opus 5.5?
Claude Opus 5.5 leads the public coding lane, 80.1 to 27.7, with Supported evidence for both models and non-overlapping 90% intervals.
Which is better for agentic tasks, Claude Haiku 4.5 or Claude Opus 5.5?
Claude Opus 5.5 leads the public agentic tasks lane, 82.9 to 29.1, with Supported evidence for both models and non-overlapping 90% intervals.
Which costs less, Claude Haiku 4.5 or Claude Opus 5.5?
For the stated presets, chat costs $0.0035 on Claude Haiku 4.5 and $0.014 on Claude Opus 5.5; repository review costs $0.065 and $0.26; the cache-heavy agent loop costs $0.09 and $0.32. Claude Haiku 4.5 does not fit this workload in one request.
Which has the larger context window, Claude Haiku 4.5 or Claude Opus 5.5?
Claude Opus 5.5 has the larger documented context window: 1M, compared with 200K.
Related comparisons
Last updated September 22, 2026
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