Long documents
Prompts that approach the documented context limit
Ornith-1.5-9B
Ornith-1.5-9B has the larger documented context window.
Confidence: documented
Ornith-1.5-9B vs Step 3.7 Flash
Updated October 2, 2026. Rank says Step 3.7 Flash 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
Decision reading
Step 3.7 Flash has the higher public point estimate, 44.85 versus 28.63. Their conditional score ranges overlap. These ranges do not establish rank confidence. 6 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
- Shared results
- 6
- Ornith-1.5-9B only
- 10
- Step 3.7 Flash only
- 5
- Like-for-like categories
- 0 / 8
Estimated: Ornith-1.5-9B and Step 3.7 Flash. 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.
Show secondary and unsupported calls
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: limitedAgentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Ornith-1.5-9B and Step 3.7 Flash are scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.
Confidence: limitedChat 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: rate-fallbackRepository 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.
—Ornith-1.5-9B32.7Step 3.7 Flash
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.
10 Ornith-1.5-9B only
6 Shared
5 Step 3.7 Flash only
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.
BrowseCompAgentic
Normalized gap 19.4Ornith-1.5-9B:56.4%Step 3.7 Flash:75.8%SWE-bench ProCoding
Normalized gap 8.8Ornith-1.5-9B:47.5%Step 3.7 Flash:56.3%
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-1.5-9B
- 18.0
- Estimated · #101/119
- Step 3.7 Flash
- 35.8
- Estimated · #67/119
- Basis
- BenchAlign v5.8 lane · 7 vs 7 public rows
- Reading
- Directional only
Knowledge
Directional only- Ornith-1.5-9B
- 30.6
- Estimated · #134/171
- Step 3.7 Flash
- 43.9
- Estimated · #85/171
- Basis
- BenchAlign v5.8 lane · 4 vs 0 public rows
- Reading
- Directional only
Coding
Not comparable- Ornith-1.5-9B
- Not ranked
- Step 3.7 Flash
- 32.7
- Estimated · #88/144
- Basis
- BenchAlign v5.8 lane · 5 vs 2 public rows
- Reading
- Not comparable
Reasoning
Not comparable- Ornith-1.5-9B
- Not ranked
- Step 3.7 Flash
- 73.0
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Ornith-1.5-9B
- Not ranked
- Step 3.7 Flash
- 72.0
- Unranked · 3 rankable rows
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Ornith-1.5-9B
- Not ranked
- Step 3.7 Flash
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Ornith-1.5-9B
- Not ranked
- Step 3.7 Flash
- 80.6
- #53/125
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Ornith-1.5-9B
- Not ranked
- Step 3.7 Flash
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Ornith-1.5-9B | Step 3.7 Flash | Basis | Reading |
|---|---|---|---|---|
| Agentic | 18.0Estimated · #101/119 | 35.8Estimated · #67/119 | Directional onlyBenchAlign v5.8 lane · 7 vs 7 public rows | Directional only |
| Knowledge | 30.6Estimated · #134/171 | 43.9Estimated · #85/171 | Directional onlyBenchAlign v5.8 lane · 4 vs 0 public rows | Directional only |
| Coding | Not ranked | 32.7Estimated · #88/144 | Not comparableBenchAlign v5.8 lane · 5 vs 2 public rows | Not comparable |
| Reasoning | Not ranked | 73.0Unranked · 2 rankable rows | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | Not ranked | 72.0Unranked · 3 rankable rows | 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 | 80.6#53/125 | 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-1.5-9B
- Self-hosted; infrastructure cost varies
- Fits in one request
- Step 3.7 Flash
- $0.00077
- Fits in one request
Ornith-1.5-9B has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- Ornith-1.5-9B
- Self-hosted; infrastructure cost varies
- Fits in one request
- Step 3.7 Flash
- $0.01345
- Fits in one request
Ornith-1.5-9B has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Ornith-1.5-9B
- Self-hosted; infrastructure cost varies
- Fits in one request
- Cached-input rate unavailable
- Step 3.7 Flash
- $0.0555
- Fits in one request
- Cached input priced at the published list-input rate
Step 3.7 Flash has no published cached-input rate, so cached tokens use its listed input 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-1.5-9BStep 3.7 Flash
Context window
Maximum documented context; output-token limits may be lower.
Ornith-1.5-9B
Step 3.7 Flash
256K
API model ID
Ornith-1.5-9B
Not sourced
Step 3.7 Flash
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Ornith-1.5-9B
No comparable hosted API rate
Ornith-1.5-9B model cardStep 3.7 Flash
Not published
Documented inputs
Ornith-1.5-9B
Not sourced
Step 3.7 Flash
Not sourced
Documented outputs
Ornith-1.5-9B
Not sourced
Step 3.7 Flash
Not sourced
Provider availability
Ornith-1.5-9B
Not sourced
Step 3.7 Flash
Not sourced
Reasoning profile
Ornith-1.5-9B
Reasoning
Step 3.7 Flash
Reasoning
Weight access
Ornith-1.5-9B
Open Weight
Step 3.7 Flash
Open Weight
License
Ornith-1.5-9B
Open Weight
Step 3.7 Flash
Open Weight
Release date
Ornith-1.5-9B
2026-08-18
Step 3.7 Flash
2026-05-29
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
- Step 3.7 Flash has the higher public point estimate, 44.85 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
- Ornith-1.5-9B has the larger documented window (262K).
Run the same representative tasks against both endpoints before changing production traffic.
Questions
Which is better, Ornith-1.5-9B or Step 3.7 Flash?
Step 3.7 Flash has the higher public point estimate, 44.85 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-1.5-9B or Step 3.7 Flash?
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-1.5-9B or Step 3.7 Flash?
Step 3.7 Flash scores higher for agentic tasks on the public lane, 35.8 to 18. Ornith-1.5-9B and Step 3.7 Flash 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-1.5-9B or Step 3.7 Flash?
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-1.5-9B or Step 3.7 Flash?
Ornith-1.5-9B has the larger documented context window: 262K, compared with 256K.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence21 rows
Agentic
Terminal-Bench 2.1
Ornith-1.5-9B46.2%SourceStep 3.7 Flash59.5%SourceStep 3.7 Flash leads this result
HLE w/ tools
Ornith-1.5-9B30.5%SourceStep 3.7 Flash47.2%SourceStep 3.7 Flash leads this result
MCP Atlas
Ornith-1.5-9B54.2%SourceStep 3.7 Flash—Not directly comparable
Toolathlon-Verified
Ornith-1.5-9B41.2%SourceStep 3.7 Flash—Not directly comparable
WideResearch
Ornith-1.5-9B59.5%SourceStep 3.7 Flash—Not directly comparable
BrowseComp
Ornith-1.5-9B56.4%SourceStep 3.7 Flash75.8%SourceStep 3.7 Flash leads this result
Claw-Eval
Ornith-1.5-9B66.5%SourceStep 3.7 Flash67.1%SourceStep 3.7 Flash leads this result
DeepSearchQA
Ornith-1.5-9B—Step 3.7 Flash92.8%SourceNot directly comparable
Toolathlon
Ornith-1.5-9B—Step 3.7 Flash49.5%SourceNot directly comparable
Gert Labs
Ornith-1.5-9B—Step 3.7 Flash51.57%SourceNot directly comparable
Coding
Terminal-Bench 2.1
Ornith-1.5-9B46.2%SourceStep 3.7 Flash59.5%SourceStep 3.7 Flash leads this result
SWE-bench Verified
Ornith-1.5-9B70.6%SourceStep 3.7 Flash—Not directly comparable
SWE-bench Pro
Ornith-1.5-9B47.5%SourceStep 3.7 Flash56.3%SourceStep 3.7 Flash leads this result
SWE Multilingual
Ornith-1.5-9B54.4%SourceStep 3.7 Flash—Not directly comparable
NL2Repo
Ornith-1.5-9B32.4%SourceStep 3.7 Flash—Not directly comparable
Multimodal
Knowledge
21 public results · 6 shared
Watch Ornith-1.5-9B vs Step 3.7 Flash
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Last updated October 2, 2026