Agentic
Not comparable- Celeris-1
- Not ranked
- Claude Opus 5
- 77.4
- Supported · #2/151
- Basis
- BenchAlign lane · 0 vs 19 public rows
- Reading
- Not comparable
Celeris-1 vs Claude Opus 5
Updated September 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
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.
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
Claude Opus 5 has the larger documented context window.
Confidence: documented
Show secondary and unsupported calls
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Celeris-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
Celeris-1 is not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limited
Chat turn cost
1K fresh input + 500 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. Celeris-1 does not fit this workload in one request.
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. Celeris-1 does not fit this workload in one request. Celeris-1 has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback
Repository review cost
50K fresh input + 3K 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. Celeris-1 does not fit this workload in one request.
Confidence: listed-rates
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
4 Celeris-1 only
73 Claude Opus 5 only
- Shared results
- 0
- Celeris-1 only
- 4
- Claude Opus 5 only
- 73
- 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- Celeris-1
- Not ranked
- Claude Opus 5
- 75.6
- Supported · #3/183
- Basis
- BenchAlign lane · 0 vs 16 public rows
- Reading
- Not comparable
Reasoning
Not comparable- Celeris-1
- 47.8
- Unranked · 3 rankable rows
- Claude Opus 5
- 75.6
- #13/22
- Basis
- Provisional lane · 0 vs 2 weighted rows
- Reading
- Not comparable
Knowledge
Not comparable- Celeris-1
- Not ranked
- Claude Opus 5
- 82.1
- Supported · #3/181
- Basis
- BenchAlign lane · 1 vs 19 public rows
- Reading
- Not comparable
Math
Not comparable- Celeris-1
- Not ranked
- Claude Opus 5
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Celeris-1
- Not ranked
- Claude Opus 5
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Celeris-1
- Not ranked
- Claude Opus 5
- 88.7
- #2/48
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Celeris-1
- Not ranked
- Claude Opus 5
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Celeris-1 | Claude Opus 5 | Basis | Reading |
|---|---|---|---|---|
| Agentic | Not ranked | 77.4Supported · #2/151 | Not comparableBenchAlign lane · 0 vs 19 public rows | Not comparable |
| Coding | Not ranked | 75.6Supported · #3/183 | Not comparableBenchAlign lane · 0 vs 16 public rows | Not comparable |
| Reasoning | 47.8Unranked · 3 rankable rows | 75.6#13/22 | Not comparableProvisional lane · 0 vs 2 weighted rows | Not comparable |
| Knowledge | Not ranked | 82.1Supported · #3/181 | Not comparableBenchAlign lane · 1 vs 19 public rows | Not comparable |
| Math | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | Not ranked | 88.7#2/48 | Not comparableProvisional lane · 0 vs 1 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.
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
- Celeris-1
- $0.00055
- Does not fit in one request
- Claude Opus 5
- $0.0175
- Fits in one request
Celeris-1 does not fit this workload in one request.
Repository review
50K fresh input + 3K output tokens
- Celeris-1
- $0.0121
- Does not fit in one request
- Claude Opus 5
- $0.325
- Fits in one request
Celeris-1 does not fit this workload in one request.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Celeris-1
- $0.051
- Does not fit in one request
- Cached input priced at the published list-input rate
- Claude Opus 5
- $0.45
- Fits in one request
Celeris-1 does not fit this workload in one request. Celeris-1 has no published cached-input rate, so cached tokens use its listed input rate.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationCeleris-1Claude Opus 5
Context window
Maximum documented context; output-token limits may be lower.
Celeris-1
131,072 tokens
Celeris-1 model guideClaude Opus 5
API model ID
Celeris-1
celeris-1
Celeris-1 model guideClaude Opus 5
claude-opus-5
Anthropic model overviewCached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Celeris-1
Not published
Celeris API pricingClaude Opus 5
$0.5 per 1M cached input tokens
Claude API pricingDocumented inputs
Celeris-1
text, image
Celeris-1 model guideClaude Opus 5
text, image
Anthropic model overviewDocumented outputs
Celeris-1
Claude Opus 5
Provider availability
Celeris-1
Generally Available · Celeris OpenAI-compatible API (United States)
Celeris availabilityClaude Opus 5
Generally Available · Claude API
Anthropic model overviewReasoning profile
Celeris-1
Non-Reasoning
Claude Opus 5
Reasoning
Weight access
Celeris-1
Proprietary
Claude Opus 5
Proprietary
License
Celeris-1
Proprietary
Claude Opus 5
Proprietary
Release date
Celeris-1
2026-07-22
Claude Opus 5
2026-07-24
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: $0.0121 vs $0.325. Cache-heavy agent loop: $0.051 vs $0.45.
- Context tradeoff
- Claude Opus 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 evidence77 rows
Agentic
Terminal-Bench 3.0
Celeris-1—Claude Opus 542.7%SourceNot directly comparable
BrowseComp
Celeris-1—Claude Opus 590.8%SourceNot directly comparable
HLE w/ tools
Celeris-1—Claude Opus 564.7%SourceNot directly comparable
DeepSearchQA
Celeris-1—Claude Opus 595.0%SourceNot directly comparable
DRACO
Celeris-1—Claude Opus 588.6%SourceNot directly comparable
BrowseComp (10-agent, prerelease)
Celeris-1—Claude Opus 593.6%SourceNot directly comparable
OSWorld 2.0
Celeris-1—Claude Opus 570.6%SourceNot directly comparable
MCP Atlas
Celeris-1—Claude Opus 585.8%SourceNot directly comparable
MCP-Atlas claim coverage
Celeris-1—Claude Opus 589.1%SourceNot directly comparable
LAB all-pass (Anthropic harness)
Celeris-1—Claude Opus 523.58%SourceNot directly comparable
LAB criterion-pass (Anthropic harness)
Celeris-1—Claude Opus 593.74%SourceNot directly comparable
LAB all-pass (Harvey held-out)
Celeris-1—Claude Opus 511.7%SourceNot directly comparable
LAB criterion-pass (Harvey held-out)
Celeris-1—Claude Opus 594.1%SourceNot directly comparable
Toolathlon-Verified
Celeris-1—Claude Opus 580.6%SourceNot directly comparable
Toolathlon Verified Pass@3
Celeris-1—Claude Opus 587.0%SourceNot directly comparable
Toolathlon Verified Pass³
Celeris-1—Claude Opus 573.1%SourceNot directly comparable
Toolathlon Verified avg. turns
Celeris-1—Claude Opus 523.5 turnsSourceNot directly comparable
AutomationBench
Celeris-1—Claude Opus 526.0%SourceNot directly comparable
Terminal-Bench 2.1 (Vals)
Celeris-1—Claude Opus 584.6%SourceNot directly comparable
Coding
Bug Hunt Bench
Celeris-1—Claude Opus 527 fixesSourceNot directly comparable
SWE-bench Verified
Celeris-1—Claude Opus 596%SourceNot directly comparable
SWE-bench Pro
Celeris-1—Claude Opus 579.2%SourceNot directly comparable
SWE Multilingual
Celeris-1—Claude Opus 589.5%SourceNot directly comparable
SWE Multimodal
Celeris-1—Claude Opus 559.4%SourceNot directly comparable
deepSwe
Celeris-1—Claude Opus 568.8%SourceNot directly comparable
FrontierCode 1.1 Main
Celeris-1—Claude Opus 553.4%SourceNot directly comparable
FrontierCode 1.1 Extended
Celeris-1—Claude Opus 563.6%SourceNot directly comparable
FrontierSWE v2
Celeris-1—Claude Opus 552.0%SourceNot directly comparable
ProgramBench (episode 1)
Celeris-1—Claude Opus 583.0%SourceNot directly comparable
ProgramBench
Celeris-1—Claude Opus 593.0%SourceNot directly comparable
cursorBench32
Celeris-1—Claude Opus 570.0%SourceNot directly comparable
VulcanBench v3
Celeris-1—Claude Opus 587.0%SourceNot directly comparable
VulcanBench CII v1
Celeris-1—Claude Opus 596.4%SourceNot directly comparable
LiveCodeBench (Vals)
Celeris-1—Claude Opus 589.0%SourceNot directly comparable
SWE-bench (Vals)
Celeris-1—Claude Opus 597.0%SourceNot directly comparable
Reasoning
Knowledge
MMLU-Pro
Celeris-175.9%SourceClaude Opus 5—Not directly comparable
HLE
Celeris-1—Claude Opus 564.7%SourceNot directly comparable
HLE w/o tools
Celeris-1—Claude Opus 556.3%SourceNot directly comparable
HLE-Verified
Celeris-1—Claude Opus 554.4%SourceNot directly comparable
LABBench2
Celeris-1—Claude Opus 584.2%SourceNot directly comparable
HealthBench (raw)
Celeris-1—Claude Opus 567.1%SourceNot directly comparable
HealthBench (length-adjusted)
Celeris-1—Claude Opus 557.8%SourceNot directly comparable
HealthBench Professional
Celeris-1—Claude Opus 559.8%SourceNot directly comparable
HealthBench Professional (raw)
Celeris-1—Claude Opus 573.4%SourceNot directly comparable
BioMysteryBench (human-solvable)
Celeris-1—Claude Opus 590.1%SourceNot directly comparable
BioMysteryBench (human-difficult)
Celeris-1—Claude Opus 549.4%SourceNot directly comparable
SpatialBench Verified
Celeris-1—Claude Opus 572.5%SourceNot directly comparable
SingleCellBench
Celeris-1—Claude Opus 560.6%SourceNot directly comparable
ProteinGym Hard
Celeris-1—Claude Opus 547.7%SourceNot directly comparable
Protein Design
Celeris-1—Claude Opus 542.5%SourceNot directly comparable
Organic chemistry V2
Celeris-1—Claude Opus 561.6%SourceNot directly comparable
Protocols (troubleshooting)
Celeris-1—Claude Opus 561.1%SourceNot directly comparable
Protocols (understanding)
Celeris-1—Claude Opus 578.4%SourceNot directly comparable
GPQA Diamond (Vals)
Celeris-1—Claude Opus 593.4%SourceNot directly comparable
MMLU-Pro (Vals)
Celeris-1—Claude Opus 591.6%SourceNot directly comparable
Math
GSM8K
Celeris-193.7%SourceClaude Opus 5—Not directly comparable
IMO 2026
Celeris-1—Claude Opus 542/42SourceNot directly comparable
RiemannBench (no tools)
Celeris-1—Claude Opus 560.0%SourceNot directly comparable
RiemannBench (tools)
Celeris-1—Claude Opus 579.0%SourceNot directly comparable
ArXivMath Jun. 2026 (no tools)
Celeris-1—Claude Opus 590.8%SourceNot directly comparable
ArXivMath Jun. 2026 (tools)
Celeris-1—Claude Opus 591.3%SourceNot directly comparable
Multilingual
Multimodal
Chartography (no tools)
Celeris-1—Claude Opus 529.6%SourceNot directly comparable
Chartography (tools)
Celeris-1—Claude Opus 583.0%SourceNot directly comparable
BenchCAD Vision2Code (no tools)
Celeris-1—Claude Opus 50.366SourceNot directly comparable
BenchCAD Vision2Code (tools)
Celeris-1—Claude Opus 50.821SourceNot directly comparable
GDP.pdf (no tools)
Celeris-1—Claude Opus 583.4%SourceNot directly comparable
GDP.pdf (tools)
Celeris-1—Claude Opus 585.5%SourceNot directly comparable
OfficeQA
Celeris-1—Claude Opus 578.1%SourceNot directly comparable
OfficeQA Pro
Celeris-1—Claude Opus 566.9%SourceNot directly comparable
Instruction following
IFEval
Celeris-180.8%SourceClaude Opus 5—Not directly comparable
Frequently asked questions
Which is better, Celeris-1 or Claude Opus 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, Celeris-1 or Claude Opus 5?
Celeris-1 is not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, Celeris-1 or Claude Opus 5?
Celeris-1 is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, Celeris-1 or Claude Opus 5?
For the stated presets, chat costs $0.00055 on Celeris-1 and $0.0175 on Claude Opus 5; repository review costs $0.0121 and $0.325; the cache-heavy agent loop costs $0.051 and $0.45. Celeris-1 does not fit this workload in one request. Celeris-1 has no published cached-input rate, so cached tokens use its listed input rate.
Which has the larger context window, Celeris-1 or Claude Opus 5?
Claude Opus 5 has the larger documented context window: 1M, compared with 131,072 tokens.
Related comparisons
Last updated September 4, 2026
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