Agentic
Directional only- Ornith-1.0-397B
- 77.5
- Step 3.7 Flash
- 66.4
- Weighted basis
- 1 vs 2 rows
- Reading
- Directional only
Ornith-1.0-397B vs Step 3.7 Flash
Updated August 13, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
4 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.
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
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.
Confidence: limited
Long documents
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documented
Chat 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-rates
Cache-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-fallback
Repository 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
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
3 Ornith-1.0-397B only
4 Shared
7 Step 3.7 Flash only
- Shared results
- 4
- Ornith-1.0-397B only
- 3
- Step 3.7 Flash only
- 7
- Like-for-like categories
- 0 / 8
2 categories use different evidence sets. Those rows remain visible for coverage context but do not name a winner.
Category results, on a stated basis
Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.
Coding
Directional only- Ornith-1.0-397B
- 74.6
- Step 3.7 Flash
- 56.3
- Weighted basis
- 2 vs 1 rows
- Reading
- Directional only
Reasoning
Not comparable- Ornith-1.0-397B
- Not measured
- Step 3.7 Flash
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Knowledge
Not comparable- Ornith-1.0-397B
- Not measured
- Step 3.7 Flash
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Math
Not comparable- Ornith-1.0-397B
- Not measured
- Step 3.7 Flash
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multilingual
Not comparable- Ornith-1.0-397B
- Not measured
- Step 3.7 Flash
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multimodal
Not comparable- Ornith-1.0-397B
- Not measured
- Step 3.7 Flash
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Instruction following
Not comparable- Ornith-1.0-397B
- Not measured
- Step 3.7 Flash
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
| Category | Ornith-1.0-397B | Step 3.7 Flash | Weighted basis | Reading |
|---|---|---|---|---|
| Agentic | 77.5 | 66.4 | Directional only1 vs 2 rows | Directional only |
| Coding | 74.6 | 56.3 | Directional only2 vs 1 rows | Directional only |
| Reasoning | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Knowledge | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Math | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multilingual | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multimodal | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Instruction following | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
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.
Terminal-Bench 2.0
Agentic
Ornith-1.0-397B: 77.5%Step 3.7 Flash: 59.5%Normalized gap 18.0Ornith-1.0-397B source Step 3.7 Flash sourceSWE-bench Pro
Coding
Ornith-1.0-397B: 62.2%Step 3.7 Flash: 56.3%Normalized gap 5.9Ornith-1.0-397B source Step 3.7 Flash source
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-1.0-397B
- Self-hosted; infrastructure cost varies
- Fits in one request
- Step 3.7 Flash
- $0.00077
- Fits in one request
Ornith-1.0-397B has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- Ornith-1.0-397B
- Self-hosted; infrastructure cost varies
- Fits in one request
- Step 3.7 Flash
- $0.01345
- Fits in one request
Ornith-1.0-397B has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Ornith-1.0-397B
- 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-1.0-397B has no comparable published API token rate.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationOrnith-1.0-397BStep 3.7 Flash
Context window
Maximum documented context; output-token limits may be lower.
Ornith-1.0-397B
256K
Step 3.7 Flash
256K
API model ID
Ornith-1.0-397B
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-1.0-397B
No comparable hosted API rate
Step 3.7 Flash
Not published
Documented inputs
Ornith-1.0-397B
Not sourced
Step 3.7 Flash
Not sourced
Documented outputs
Ornith-1.0-397B
Not sourced
Step 3.7 Flash
Not sourced
Provider availability
Ornith-1.0-397B
Not sourced
Step 3.7 Flash
Not sourced
Reasoning profile
Ornith-1.0-397B
Reasoning
Step 3.7 Flash
Reasoning
Weight access
Ornith-1.0-397B
Open Weight
Step 3.7 Flash
Open Weight
License
Ornith-1.0-397B
Open Weight
Step 3.7 Flash
Open Weight
Release date
Ornith-1.0-397B
2026-06-01
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
- At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- Both models list 256K.
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 evidence14 rows
Agentic
Terminal-Bench 2.0
Ornith-1.0-397B77.5%SourceStep 3.7 Flash59.5%SourceOrnith-1.0-397B leads this result
Claw-Eval
Ornith-1.0-397B77.1%SourceStep 3.7 Flash67.1%SourceOrnith-1.0-397B leads this result
BrowseComp
Ornith-1.0-397B—Step 3.7 Flash75.8%SourceNot directly comparable
DeepSearchQA
Ornith-1.0-397B—Step 3.7 Flash92.8%SourceNot directly comparable
Toolathlon
Ornith-1.0-397B—Step 3.7 Flash49.5%SourceNot directly comparable
HLE w/ tools
Ornith-1.0-397B—Step 3.7 Flash47.2%SourceNot directly comparable
Gert Labs
Ornith-1.0-397B—Step 3.7 Flash51.57%SourceNot directly comparable
Coding
SWE-bench Verified
Ornith-1.0-397B82.4%SourceStep 3.7 Flash—Not directly comparable
SWE-bench Pro
Ornith-1.0-397B62.2%SourceStep 3.7 Flash56.3%SourceOrnith-1.0-397B leads this result
SWE Multilingual
Ornith-1.0-397B78.9%SourceStep 3.7 Flash—Not directly comparable
NL2Repo
Ornith-1.0-397B48.2%SourceStep 3.7 Flash—Not directly comparable
Terminal-Bench 2.0
Ornith-1.0-397B77.5%SourceStep 3.7 Flash59.5%SourceOrnith-1.0-397B leads this result
Multimodal
Frequently asked questions
Which is better, Ornith-1.0-397B or Step 3.7 Flash?
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, Ornith-1.0-397B or Step 3.7 Flash?
The current coding averages use different weighted benchmark sets, so BenchLM does not name a winner from them. Read the shared benchmark rows directly and test the models on the same task set.
Which is better for agentic tasks, Ornith-1.0-397B or Step 3.7 Flash?
The current agentic tasks averages use different weighted benchmark sets, so BenchLM does not name a winner from them. Read the shared benchmark rows directly and test the models on the same task set.
Which costs less, Ornith-1.0-397B 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-1.0-397B or Step 3.7 Flash?
Both models list the same context window, 256K.
Related comparisons
Last updated August 13, 2026
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