Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Ornith-1.5-9B is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limited
Ornith-1.5-35B-A3B vs Ornith-1.5-9B
Updated October 2, 2026. Rank says Ornith-1.5-35B-A3B is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty. This is a same-family comparison, so migration details appear when the source data supports them.
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
Decision reading
Ornith-1.5-35B-A3B has the higher public point estimate, 32.61 versus 28.63. Their conditional score ranges overlap. These ranges do not establish rank confidence. 16 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
- Shared results
- 16
- Ornith-1.5-35B-A3B only
- 2
- Ornith-1.5-9B only
- 0
- Like-for-like categories
- 0 / 8
Estimated: Ornith-1.5-35B-A3B and Ornith-1.5-9B. Conditional ranges do not establish rank confidence.How 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.
No workload recommendation clears the current evidence threshold.
Use the matched evidence, workload costs, and sourced specifications below instead of treating a point score as a universal answer.
Show secondary and unsupported calls
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Ornith-1.5-35B-A3B and Ornith-1.5-9B are scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.
Confidence: limitedLong documents
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documentedChat turn cost
1K fresh input + 500 output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-ratesCache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-ratesRepository review cost
50K fresh input + 3K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
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.
24.0Ornith-1.5-35B-A3B—Ornith-1.5-9B
Not comparable · BenchAlign v5.8
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.
2 Ornith-1.5-35B-A3B only
16 Shared
2 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.
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.
SWE MultilingualCoding
Normalized gap 17.0Ornith-1.5-35B-A3B:71.4%Ornith-1.5-9B:54.4%SWE-bench ProCoding
Normalized gap 12.1Ornith-1.5-35B-A3B:59.6%Ornith-1.5-9B:47.5%BrowseCompAgentic
Normalized gap 11.2Ornith-1.5-35B-A3B:67.6%Ornith-1.5-9B:56.4%SWE-bench VerifiedCoding
Normalized gap 8.4Ornith-1.5-35B-A3B:79%Ornith-1.5-9B:70.6%HLEKnowledge
Normalized gap 5.4Ornith-1.5-35B-A3B:25.6%Ornith-1.5-9B:20.2%
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 v5.8 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
Directional only- Ornith-1.5-35B-A3B
- 23.5
- Estimated · #95/119
- Ornith-1.5-9B
- 18.0
- Estimated · #101/119
- Basis
- BenchAlign v5.8 lane · 7 vs 7 public rows
- Reading
- Directional only
Knowledge
Directional only- Ornith-1.5-35B-A3B
- 34.5
- Estimated · #119/171
- Ornith-1.5-9B
- 30.6
- Estimated · #134/171
- Basis
- BenchAlign v5.8 lane · 4 vs 4 public rows
- Reading
- Directional only
Coding
Not comparable- Ornith-1.5-35B-A3B
- 24.0
- Estimated · #110/144
- Ornith-1.5-9B
- Not ranked
- Basis
- BenchAlign v5.8 lane · 7 vs 5 public rows
- Reading
- Not comparable
Reasoning
Not comparable- Ornith-1.5-35B-A3B
- Not ranked
- Ornith-1.5-9B
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Ornith-1.5-35B-A3B
- Not ranked
- Ornith-1.5-9B
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Ornith-1.5-35B-A3B
- Not ranked
- Ornith-1.5-9B
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Ornith-1.5-35B-A3B
- Not ranked
- Ornith-1.5-9B
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Ornith-1.5-35B-A3B
- Not ranked
- Ornith-1.5-9B
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Ornith-1.5-35B-A3B | Ornith-1.5-9B | Basis | Reading |
|---|---|---|---|---|
| Agentic | 23.5Estimated · #95/119 | 18.0Estimated · #101/119 | Directional onlyBenchAlign v5.8 lane · 7 vs 7 public rows | Directional only |
| Knowledge | 34.5Estimated · #119/171 | 30.6Estimated · #134/171 | Directional onlyBenchAlign v5.8 lane · 4 vs 4 public rows | Directional only |
| Coding | 24.0Estimated · #110/144 | Not ranked | Not comparableBenchAlign v5.8 lane · 7 vs 5 public rows | Not comparable |
| Reasoning | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | 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 |
| 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 v5.8) 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.
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
- Ornith-1.5-35B-A3B
- Self-hosted; infrastructure cost varies
- Fits in one request
- Ornith-1.5-9B
- Self-hosted; infrastructure cost varies
- Fits in one request
Ornith-1.5-35B-A3B has no comparable published API token rate. Ornith-1.5-9B has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- Ornith-1.5-35B-A3B
- Self-hosted; infrastructure cost varies
- Fits in one request
- Ornith-1.5-9B
- Self-hosted; infrastructure cost varies
- Fits in one request
Ornith-1.5-35B-A3B has no comparable published API token rate. Ornith-1.5-9B has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Ornith-1.5-35B-A3B
- Self-hosted; infrastructure cost varies
- Fits in one request
- Cached-input rate unavailable
- Ornith-1.5-9B
- Self-hosted; infrastructure cost varies
- Fits in one request
- Cached-input rate unavailable
Ornith-1.5-35B-A3B has no comparable published API token rate. Ornith-1.5-9B has no comparable published API token rate.
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.
SpecificationOrnith-1.5-35B-A3BOrnith-1.5-9B
Context window
Maximum documented context; output-token limits may be lower.
Ornith-1.5-35B-A3B
Ornith-1.5-9B
API model ID
Ornith-1.5-35B-A3B
Not sourced
Ornith-1.5-9B
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Ornith-1.5-35B-A3B
No comparable hosted API rate
Ornith-1.5-35B-A3B model cardOrnith-1.5-9B
No comparable hosted API rate
Ornith-1.5-9B model cardDocumented inputs
Ornith-1.5-35B-A3B
Not sourced
Ornith-1.5-9B
Not sourced
Documented outputs
Ornith-1.5-35B-A3B
Not sourced
Ornith-1.5-9B
Not sourced
Provider availability
Ornith-1.5-35B-A3B
Not sourced
Ornith-1.5-9B
Not sourced
Reasoning profile
Ornith-1.5-35B-A3B
Reasoning
Ornith-1.5-9B
Reasoning
Weight access
Ornith-1.5-35B-A3B
Open Weight
Ornith-1.5-9B
Open Weight
License
Ornith-1.5-35B-A3B
Open Weight
Ornith-1.5-9B
Open Weight
Release date
Ornith-1.5-35B-A3B
2026-08-18
Ornith-1.5-9B
2026-08-18
If you are choosing between sibling variants
- Deployment change
- Both entries list Ornith AI as the provider. Confirm endpoint, model ID, limits, and feature support before switching.
- Quality signal
- Ornith-1.5-35B-A3B has the higher public point estimate, 32.61 versus 28.63. Their conditional score ranges overlap. These ranges do not establish rank confidence.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- Both models list 262K.
Run the same representative tasks against both endpoints before changing production traffic.
Questions
Which is better, Ornith-1.5-35B-A3B or Ornith-1.5-9B?
Ornith-1.5-35B-A3B has the higher public point estimate, 32.61 versus 28.63. Their conditional score ranges overlap. These ranges do not establish rank confidence. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, Ornith-1.5-35B-A3B or Ornith-1.5-9B?
Ornith-1.5-9B is not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, Ornith-1.5-35B-A3B or Ornith-1.5-9B?
Ornith-1.5-35B-A3B scores higher for agentic tasks on the public lane, 23.5 to 18. Ornith-1.5-35B-A3B and Ornith-1.5-9B are 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.
Which costs less, Ornith-1.5-35B-A3B or Ornith-1.5-9B?
Both models do not have comparable published API token rates, so this page does not name a universal price winner.
Which has the larger context window, Ornith-1.5-35B-A3B or Ornith-1.5-9B?
Both models list the same context window, 262K.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence18 rows
Agentic
Terminal-Bench 2.1
Shared sourceOrnith-1.5-35B-A3B67.8%Ornith-1.5-9B46.2%Ornith-1.5-35B-A3B leads this result
HLE w/ tools
Shared sourceOrnith-1.5-35B-A3B33.4%Ornith-1.5-9B30.5%Ornith-1.5-35B-A3B leads this result
MCP Atlas
Shared sourceOrnith-1.5-35B-A3B70.2%Ornith-1.5-9B54.2%Ornith-1.5-35B-A3B leads this result
Toolathlon-Verified
Shared sourceOrnith-1.5-35B-A3B48.7%Ornith-1.5-9B41.2%Ornith-1.5-35B-A3B leads this result
WideResearch
Shared sourceOrnith-1.5-35B-A3B67.8%Ornith-1.5-9B59.5%Ornith-1.5-35B-A3B leads this result
BrowseComp
Shared sourceOrnith-1.5-35B-A3B67.6%Ornith-1.5-9B56.4%Ornith-1.5-35B-A3B leads this result
Claw-Eval
Shared sourceOrnith-1.5-35B-A3B72.5%Ornith-1.5-9B66.5%Ornith-1.5-35B-A3B leads this result
Coding
Terminal-Bench 2.1
Shared sourceOrnith-1.5-35B-A3B67.8%Ornith-1.5-9B46.2%Ornith-1.5-35B-A3B leads this result
SWE-bench Verified
Shared sourceOrnith-1.5-35B-A3B79%Ornith-1.5-9B70.6%Ornith-1.5-35B-A3B leads this result
SWE-bench Pro
Shared sourceOrnith-1.5-35B-A3B59.6%Ornith-1.5-9B47.5%Ornith-1.5-35B-A3B leads this result
SWE Multilingual
Shared sourceOrnith-1.5-35B-A3B71.4%Ornith-1.5-9B54.4%Ornith-1.5-35B-A3B leads this result
DeepSWE
Ornith-1.5-35B-A3B22.0%SourceOrnith-1.5-9B—Not directly comparable
frontierBench
Ornith-1.5-35B-A3B5.1%SourceOrnith-1.5-9B—Not directly comparable
NL2Repo
Shared sourceOrnith-1.5-35B-A3B46.2%Ornith-1.5-9B32.4%Ornith-1.5-35B-A3B leads this result
Knowledge
GPQA
Shared sourceOrnith-1.5-35B-A3B89.2%Ornith-1.5-9B86.4%Ornith-1.5-35B-A3B leads this result
GPQA-D
Shared sourceOrnith-1.5-35B-A3B89.2%Ornith-1.5-9B86.4%Ornith-1.5-35B-A3B leads this result
- Ornith-1.5-35B-A3B25.6%Ornith-1.5-9B20.2%
Ornith-1.5-35B-A3B leads this result
HLE w/o tools
Shared sourceOrnith-1.5-35B-A3B25.6%Ornith-1.5-9B20.2%Ornith-1.5-35B-A3B leads this result
18 public results · 16 shared
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Last updated October 2, 2026