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Ornith-1.5-397B

Released Aug 18, 2026 see all recent releases

Decision reading
Ornith-1.5-397B scores 68.5 out of 100 and ranks #20 of 221. This profile shows 18 source-displayable benchmark rows; its strongest eligible category is Agentic at #13. Published weights can be self-hosted, but infrastructure cost varies and is not a comparable API token rate.

Data as of August 19, 2026 · How the score is built

Strongest published evidence

Agentic ranks #13. Particularly useful for coding agents, browser research, and computer-use workflows.

Validate before choosing

18 published rows leave some tracked benchmark slots empty. No comparable first-party API token rate is published.

Decision snapshot

Each value carries a field reference instead of floating alone. Markers compare this model with the current ranked and priced catalog; they are not absolute quality thresholds.

Capability

68.5/100

field median 58.2

#20 of 221 ranked models

Price

Self-hosted; infrastructure cost varies

input median $1

No comparable first-party hosted token rate

Speed

Not measured

field median 97 tok/s

Time to first token not measured

Context

262Ktokens

field median 203,000

Maximum output length is tracked separately

Capability shape

Each axis shows percentile within that category’s eligible cohort. The comparison outline is the median of the six nearest public-score peers; a collapsed vertex means the category is not rank-eligible.

Ornith-1.5-397B category percentile values

  • Agentic91st percentile
  • Coding80th percentile
  • ReasoningNot eligible
  • KnowledgeNot eligible
  • MathNot eligible
  • MultilingualNot eligible
  • MultimodalNot eligible
  • Instruction followingNot eligible

The dashed outline is median of 6 nearest peers.

Eligible category ranks

  1. Agentic#13/134
  2. Coding#29/138
  3. ReasoningNot ranked
  4. KnowledgeNot ranked
  5. MathNot ranked
  6. MultilingualNot ranked
  7. MultimodalNot ranked
  8. Inst. FollowingNot ranked
Top decileTop quartileMid-fieldNot eligible

How much of this is verified

Coverage is split by category so a strong number never hides a thin evidence base. Verified means the row is tied to a published source; provisional rows remain visible but separate.

  1. Agentic7/7 verified
  2. Coding7/7 verified
  3. ReasoningNot measured
  4. Knowledge4/4 verified
  5. MathNot measured
  6. MultilingualNot measured
  7. MultimodalNot measured
  8. Inst. FollowingNot measured
Verified sourceProvisionalNot measured

Spec sheet

Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.

API model ID
Not publishedOrnith-1.5-397B model card
Context window
262KOrnith-1.5-397B model card
Maximum output
Not sourced yet
Knowledge cutoff
Not sourced yet
Input modalities
Not sourced yet
Output modalities
Not sourced yet
Parameters
Not sourced yet
Availability
Ornith publishes the MIT-licensed 397B MoE checkpoint for self-hosted use. Its official Hugging Face configuration specifies a 262,144-token context window; no first-party hosted API or token rate is published for this exact model.
Cloud regions
Not tracked yet
Lifecycle
Current
API capabilities
Tool calling, structured outputs, and batch support are not tracked yet
Prompt caching
Not documented in the pricing recordOrnith-1.5-397B model card
Self-host
Open weights available; hardware estimate not sourced
Rate limits
Not tracked yet

Deployment options

Self-host and provider-specific paths stay separate from benchmark evidence so operating constraints are visible before a score becomes the whole decision.

Published weights are available, but BenchLM does not yet have a sourced parameter and VRAM profile for this exact model. Hardware cost estimates stay unavailable until that sizing record is complete.

Estimate VRAM from known parameters

Category score record

Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.

Category scores, ranks, weighting, benchmark coverage, and evidence status
CategoryScore
AgenticRank #13 of 134Percentile 91stWeight 22%7 benchmarksVerified62.4
CodingRank #29 of 138Percentile 80thWeight 20%7 benchmarksVerified61.5
ReasoningWeight 17%0 benchmarksNot measuredNot measured
KnowledgeRank Not rankedWeight 12%4 benchmarksVerified68.0
MathWeight 5%0 benchmarksNot measuredNot measured
MultilingualWeight 7%0 benchmarksNot measuredNot measured
MultimodalWeight 12%0 benchmarksNot measuredNot measured
Inst. FollowingWeight 5%0 benchmarksNot measuredNot measured

Benchmark ledger

Coding opens by default. The marker compares each value with the best source-verified result in the catalog; provisional leaders do not set the reference. Expand the remaining categories for every published row.

Coding7 rows
Coding benchmark values, best verified comparison, weight, and source status
SWE-bench VerifiedSoftware Engineering Benchmark VerifiedScore86%Versus best verified row

Best verified: Claude Opus 5 · 96%

Gap10 behindWeightWeighted 16%
SWE-bench ProScore65.1%Versus best verified row

Best verified: Claude Mythos 5 · 80.3%

Gap15.2 behindWeightWeighted 10%
Terminal-Bench 2.1Terminal-Bench 2.1 (provider run)Score86.1%Versus best verified row

Best verified: GLM-5.3 · 88.2%

Gap2.1 behindWeightDisplay only
SWE MultilingualScore79.6%Versus best verified row

Best verified: Claude Opus 5 · 89.5%

Gap9.9 behindWeightDisplay only
deepSweScore56%Versus best verified row

Best verified: GPT-5.6 Sol · 72.7%

Gap16.7 behindWeightDisplay only
frontierBenchScore13.5%Versus best verified row

Best verified: Ornith-1.5-397B · 13.5%

GapBest verifiedWeightDisplay only
NL2RepoScore59.5%Versus best verified row

Best verified: DeepSeek V4 Pro 0813 · 61.5%

Gap2 behindWeightDisplay only
Agentic7 rows
Agentic benchmark values, best verified comparison, weight, and source status
BrowseCompScore86.6%Versus best verified row

Best verified: GPT-5.6 Sol · 92.2%

Gap5.6 behindWeightWeighted 28%
Terminal-Bench 2.1Terminal-Bench 2.1 (provider run)Score86.1%Versus best verified row

Best verified: GLM-5.3 · 88.2%

Gap2.1 behindWeightDisplay only
HLE w/ toolsHumanity's Last Exam with toolsScore56.1%Versus best verified row

Best verified: Claude Opus 5 · 64.7%

Gap8.6 behindWeightDisplay only
MCP AtlasScore80%Versus best verified row

Best verified: Muse Spark 1.1 · 88.1%

Gap8.1 behindWeightDisplay only
Toolathlon-VerifiedScore71.2%Versus best verified row

Best verified: Claude Opus 5 · 80.6%

Gap9.4 behindWeightDisplay only
WideResearchScore80.8%Versus best verified row

Best verified: Qwen3.8 Max · 81.9%

Gap1.1 behindWeightDisplay only
Claw-EvalScore81.4%Versus best verified row

Best verified: Ornith-1.5-397B · 81.4%

GapBest verifiedWeightDisplay only
Knowledge4 rows
Knowledge benchmark values, best verified comparison, weight, and source status
HLEHumanity's Last ExamScore44.6%Versus best verified row

Best verified: Claude Opus 5 · 64.7%

Gap20.1 behindWeightWeighted 45%
GPQAGraduate-Level Google-Proof Q&AScore92.8%Versus best verified row

Best verified: Sakana Fugu-Ultra · 95.5%

Gap2.7 behindWeightWeighted 7%
GPQA-DGPQA DiamondScore92.8%Versus best verified row

Best verified: Sakana Fugu-Ultra · 95.5%

Gap2.7 behindWeightDisplay only
HLE w/o toolsHumanity's Last Exam without toolsScore44.6%Versus best verified row

Best verified: Claude Mythos 5 · 59%

Gap14.4 behindWeightDisplay only

Lineage

The sequence follows explicit supersedes links. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.

397b · 397B

How to read this profile

The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.

Ornith-1.5-397B ranks #20 of 221 on the public leaderboard with a score of 68.5/100. It does not yet have enough sourced coverage for a verified position.

Ornith-1.5-397B is a open weight model with a 262K context window. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.

Ornith publishes the MIT-licensed 397B MoE checkpoint for self-hosted use. Its official Hugging Face configuration specifies a 262,144-token context window; no first-party hosted API or token rate is published for this exact model.

Official exact-value snapshot from Ornith's August 2026 Ornith-1.5 launch page. BenchLM maps the directly comparable provider-reported rows, including the versioned Terminal-Bench 2.1, DeepSWE, and Terminal-Bench 3.0 results as distinct display evidence; the source says all Ornith-1.5 results are averaged over five runs. SWE Atlas QnA and Terminal-Bench Claude Code remain outside the current schema. The family remains unranked while independent benchmark-native coverage is unavailable.

Ornith-1.5-397B sits in the Ornith 1.5 family with Ornith-1.5-35B-A3B, Ornith-1.5-9B. Its explicit predecessor is Ornith-1.0-397B. 18 of 437 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.

Its strongest eligible category is Agentic at #13, while its lowest eligible position is Coding at #29. particularly useful for coding agents, browser research, and computer-use workflows.

Radar

Ornith-1.5-397B release history

Full release history

Frequently asked questions

How does Ornith-1.5-397B perform overall in AI benchmarks?

Ornith-1.5-397B ranks #20 out of 221 models on the public BenchAlign leaderboard, with a score of 68.5/100. Its evidence status is Estimated, and this profile shows 18 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.

Is Ornith-1.5-397B good for knowledge and understanding?

Ornith-1.5-397B has source-displayable benchmark coverage for knowledge and understanding, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.

Is Ornith-1.5-397B good for coding and programming?

Ornith-1.5-397B ranks #29 out of 138 eligible models for coding and programming, with a public category score of 61.5/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Ornith-1.5-397B good for agentic tool use and computer tasks?

Ornith-1.5-397B ranks #13 out of 134 eligible models for agentic tool use and computer tasks, with a public category score of 62.4/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Ornith-1.5-397B open source?

Ornith-1.5-397B is an open-weight model from Ornith AI. Its weights can be downloaded for local or hosted deployment, subject to the published license. Open weight does not automatically mean open source: training data and training code may remain private, and commercial restrictions can still apply.

Which sibling models are related to Ornith-1.5-397B?

Ornith-1.5-397B belongs to the Ornith 1.5 family. Related tracked variants include Ornith-1.5-35B-A3B, Ornith-1.5-9B. A sibling link indicates shared lineage or a documented configuration relationship; it does not mean the variants have identical pricing, context limits, benchmark evidence, or deployment behavior. Compare before switching.

Does Ornith-1.5-397B have full benchmark coverage on BenchLM?

No. Ornith-1.5-397B currently has 18 source-displayable rows across 437 tracked benchmark slots. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.

What is the context window size of Ornith-1.5-397B?

Ornith-1.5-397B has a documented context window of 262K. That figure is the maximum combined prompt and retained-conversation space reported for this exact model; it is not the maximum output length. The profile keeps output limits separate because providers often publish those limits independently.

Last updated August 19, 2026. Runtime fields remain blank until a sourced snapshot exists.

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