Model A

DeepReinforce AI

—

Evidence status unavailable

90% interval unavailable

Ornith-1.0-397B vs Qwen3.6 Plus

Updated August 13, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Model B

Qwen3.6 Plus

Alibaba

64.6/100

Supported · Public rank #36

90% interval 55.5–73.7

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.

5 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.

Coding work
Code generation, repair, and software-engineering tasks
Ornith-1.0-397B
Ornith-1.0-397B leads on the same 2 weighted benchmark rows.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Ornith-1.0-397B
Ornith-1.0-397B leads on the same 1 weighted benchmark row.
Confidence: limited
Long documents
Prompts that approach the documented context limit
Qwen3.6 Plus
Qwen3.6 Plus has the larger documented context window.
Confidence: documented

Show secondary and unsupported calls

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: listed-rates
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.

2 Ornith-1.0-397B only

5 Shared

39 Qwen3.6 Plus only

Shared results: 5
Ornith-1.0-397B only: 2
Qwen3.6 Plus only: 39
Like-for-like categories: 2 / 8

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.

Agentic

Like-for-like

Ornith-1.0-397B: 77.5
Qwen3.6 Plus: 61.6
Weighted basis: 1 vs 1 rows
Reading: Ornith-1.0-397B leads

Coding

Like-for-like

Ornith-1.0-397B: 74.6
Qwen3.6 Plus: 70.3
Weighted basis: 2 vs 2 rows
Reading: Ornith-1.0-397B leads

Reasoning

Not comparable

Ornith-1.0-397B: Not measured
Qwen3.6 Plus: 62.0
Weighted basis: 0 vs 1 rows
Reading: Not comparable

Knowledge

Not comparable

Ornith-1.0-397B: Not measured
Qwen3.6 Plus: 57.1
Weighted basis: 0 vs 4 rows
Reading: Not comparable

Math

Not comparable

Ornith-1.0-397B: Not measured
Qwen3.6 Plus: 60.5
Weighted basis: 0 vs 4 rows
Reading: Not comparable

Multilingual

Not comparable

Ornith-1.0-397B: Not measured
Qwen3.6 Plus: 84.7
Weighted basis: 0 vs 1 rows
Reading: Not comparable

Multimodal

Not comparable

Ornith-1.0-397B: Not measured
Qwen3.6 Plus: 79.8
Weighted basis: 0 vs 2 rows
Reading: Not comparable

Instruction following

Not comparable

Ornith-1.0-397B: Not measured
Qwen3.6 Plus: 82.3
Weighted basis: 0 vs 2 rows
Reading: Not comparable

Category averages with the server-provided evidence basis for Ornith-1.0-397B and Qwen3.6 Plus
Category	Ornith-1.0-397B	Qwen3.6 Plus	Weighted basis	Reading
Agentic	77.5	61.6	Like-for-like1 vs 1 rows	Ornith-1.0-397B leads
Coding	74.6	70.3	Like-for-like2 vs 2 rows	Ornith-1.0-397B leads
Reasoning	Not measured	62.0	Not comparable0 vs 1 rows	Not comparable
Knowledge	Not measured	57.1	Not comparable0 vs 4 rows	Not comparable
Math	Not measured	60.5	Not comparable0 vs 4 rows	Not comparable
Multilingual	Not measured	84.7	Not comparable0 vs 1 rows	Not comparable
Multimodal	Not measured	79.8	Not comparable0 vs 2 rows	Not comparable
Instruction following	Not measured	82.3	Not comparable0 vs 2 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%Qwen3.6 Plus: 61.6%Normalized gap 15.9Ornith-1.0-397B source Qwen3.6 Plus source
SWE-bench Pro
Coding
Ornith-1.0-397B: 62.2%Qwen3.6 Plus: 56.6%Normalized gap 5.6Ornith-1.0-397B source Qwen3.6 Plus source
SWE-bench Verified
Coding
Ornith-1.0-397B: 82.4%Qwen3.6 Plus: 78.8%Normalized gap 3.6Ornith-1.0-397B source Qwen3.6 Plus 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
Qwen3.6 Plus: API rate not published; Fits in one request

Ornith-1.0-397B has no comparable published API token rate. Qwen3.6 Plus 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
Qwen3.6 Plus: API rate not published; Fits in one request

Ornith-1.0-397B has no comparable published API token rate. Qwen3.6 Plus 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
Qwen3.6 Plus: API rate not published; Fits in one request; Cached-input rate unavailable

Ornith-1.0-397B has no comparable published API token rate. Qwen3.6 Plus 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-1.0-397BQwen3.6 Plus

Context window

Maximum documented context; output-token limits may be lower.

Ornith-1.0-397B

256K

Qwen3.6 Plus

API model ID

Ornith-1.0-397B

Not sourced

Qwen3.6 Plus

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

Qwen3.6 Plus

No comparable hosted API rate

Documented inputs

Ornith-1.0-397B

Not sourced

Qwen3.6 Plus

Not sourced

Documented outputs

Ornith-1.0-397B

Not sourced

Qwen3.6 Plus

Not sourced

Provider availability

Ornith-1.0-397B

Not sourced

Qwen3.6 Plus

Not sourced

Reasoning profile

Ornith-1.0-397B

Reasoning

Qwen3.6 Plus

Reasoning

Weight access

Ornith-1.0-397B

Open Weight

Qwen3.6 Plus

Proprietary

License

Ornith-1.0-397B

Open Weight

Qwen3.6 Plus

Proprietary

Release date

Ornith-1.0-397B

2026-06-01

Qwen3.6 Plus

2026-04-02

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: Qwen3.6 Plus 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 evidence46 rows

Agentic

Terminal-Bench 2.0
Ornith-1.0-397B77.5%
Source
Qwen3.6 Plus61.6%
Source
Ornith-1.0-397B leads this result
Claw-Eval
Ornith-1.0-397B77.1%
Source
Qwen3.6 Plus58.8%
Source
Ornith-1.0-397B leads this result
QwenClawBench
Ornith-1.0-397B—
Qwen3.6 Plus57.2%
Source
Not directly comparable
τ³-bench results
Ornith-1.0-397B—
Qwen3.6 Plus70.7%
Source
Not directly comparable
VITA-Bench
Ornith-1.0-397B—
Qwen3.6 Plus44.3%
Source
Not directly comparable
DeepPlanning
Ornith-1.0-397B—
Qwen3.6 Plus41.5%
Source
Not directly comparable
Toolathlon
Ornith-1.0-397B—
Qwen3.6 Plus39.8%
Source
Not directly comparable
MCP Atlas
Ornith-1.0-397B—
Qwen3.6 Plus48.2%
Source
Not directly comparable
MCP-Tasks
Ornith-1.0-397B—
Qwen3.6 Plus74.1%
Source
Not directly comparable
WideResearch
Ornith-1.0-397B—
Qwen3.6 Plus74.3%
Source
Not directly comparable
Gert Labs
Ornith-1.0-397B—
Qwen3.6 Plus50.60%
Source
Not directly comparable
ResearchClawBench
Ornith-1.0-397B—
Qwen3.6 Plus18.0%
Source
Not directly comparable

Coding

SWE-bench Verified
Ornith-1.0-397B82.4%
Source
Qwen3.6 Plus78.8%
Source
Ornith-1.0-397B leads this result
SWE-bench Pro
Ornith-1.0-397B62.2%
Source
Qwen3.6 Plus56.6%
Source
Ornith-1.0-397B leads this result
SWE Multilingual
Ornith-1.0-397B78.9%
Source
Qwen3.6 Plus73.8%
Source
Ornith-1.0-397B leads this result
NL2Repo
Ornith-1.0-397B48.2%
Source
Qwen3.6 Plus—
Not directly comparable
Terminal-Bench 2.0
Ornith-1.0-397B77.5%
Source
Qwen3.6 Plus—
Not directly comparable
LiveCodeBench v6
Ornith-1.0-397B—
Qwen3.6 Plus87.1%
Source
Not directly comparable
Vibe Code Bench
Ornith-1.0-397B—
Qwen3.6 Plus25.56%
Source
Not directly comparable
EEBench
Ornith-1.0-397B—
Qwen3.6 Plus12.7%
Source
Not directly comparable

Reasoning

AI-Needle
Ornith-1.0-397B—
Qwen3.6 Plus68.3%
Source
Not directly comparable
LongBench v2
Ornith-1.0-397B—
Qwen3.6 Plus62%
Source
Not directly comparable

Knowledge

GPQA
Ornith-1.0-397B—
Qwen3.6 Plus90.4%
Source
Not directly comparable
SuperGPQA
Ornith-1.0-397B—
Qwen3.6 Plus71.6%
Source
Not directly comparable
MMLU-Pro
Ornith-1.0-397B—
Qwen3.6 Plus88.5%
Source
Not directly comparable
MMLU-Redux
Ornith-1.0-397B—
Qwen3.6 Plus94.5%
Source
Not directly comparable
C-Eval
Ornith-1.0-397B—
Qwen3.6 Plus93.3%
Source
Not directly comparable
HLE
Ornith-1.0-397B—
Qwen3.6 Plus28.8%
Source
Not directly comparable

Math

AIME26
Ornith-1.0-397B—
Qwen3.6 Plus95.3%
Source
Not directly comparable
HMMT Feb 2025
Ornith-1.0-397B—
Qwen3.6 Plus96.7%
Source
Not directly comparable
HMMT Nov 2025
Ornith-1.0-397B—
Qwen3.6 Plus94.6%
Source
Not directly comparable
HMMT Feb 2026
Ornith-1.0-397B—
Qwen3.6 Plus87.8%
Source
Not directly comparable
MMAnswerBench
Ornith-1.0-397B—
Qwen3.6 Plus83.8%
Source
Not directly comparable
FrontierMath v2 (Tiers 1-3)
Ornith-1.0-397B—
Qwen3.6 Plus26.207%
Source
Not directly comparable
FrontierMath v2 (Tier 4)
Ornith-1.0-397B—
Qwen3.6 Plus8.333%
Source
Not directly comparable

Multilingual

MMLU-ProX
Ornith-1.0-397B—
Qwen3.6 Plus84.7%
Source
Not directly comparable
NOVA-63
Ornith-1.0-397B—
Qwen3.6 Plus57.9%
Source
Not directly comparable

Multimodal

MMMU
Ornith-1.0-397B—
Qwen3.6 Plus86.0%
Source
Not directly comparable
MMMU-Pro
Ornith-1.0-397B—
Qwen3.6 Plus78.8%
Source
Not directly comparable
MathVision
Ornith-1.0-397B—
Qwen3.6 Plus88.0%
Source
Not directly comparable
VideoMMMU
Ornith-1.0-397B—
Qwen3.6 Plus84.0%
Source
Not directly comparable
ScreenSpot Pro
Ornith-1.0-397B—
Qwen3.6 Plus68.2%
Source
Not directly comparable
CharXiv
Ornith-1.0-397B—
Qwen3.6 Plus81.5%
Source
Not directly comparable
V*
Ornith-1.0-397B—
Qwen3.6 Plus96.9%
Source
Not directly comparable

Instruction following

IFEval
Ornith-1.0-397B—
Qwen3.6 Plus94.3%
Source
Not directly comparable
IFBench
Ornith-1.0-397B—
Qwen3.6 Plus75.8%
Source
Not directly comparable

Frequently asked questions

Which is better, Ornith-1.0-397B or Qwen3.6 Plus?

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 Qwen3.6 Plus?

Ornith-1.0-397B leads the like-for-like coding comparison across 2 shared weighted benchmark rows.

Which is better for agentic tasks, Ornith-1.0-397B or Qwen3.6 Plus?

Ornith-1.0-397B leads the like-for-like agentic tasks comparison across 1 shared weighted benchmark row.

Which costs less, Ornith-1.0-397B or Qwen3.6 Plus?

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 Qwen3.6 Plus?

Qwen3.6 Plus has the larger documented context window: 1M, compared with 256K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated August 13, 2026

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Ornith-1.0-397B vs Qwen3.6 Plus

Which one for your work

Coding work

Agentic work

Long documents

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

What is actually comparable

Category results, on a stated basis

Agentic

Coding

Reasoning

Knowledge

Math

Multilingual

Multimodal

Instruction following

Shape of the matched evidence

What each workload costs

Chat turn

Repository review

Cache-heavy agent loop

Specification differences

Context window

API model ID

Cached-input rate

Documented inputs

Documented outputs

Provider availability

Reasoning profile

Weight access

License

Release date

Benchmark evidence

Agentic

Coding

Reasoning

Knowledge

Math

Multilingual

Multimodal

Instruction following

Frequently asked questions

Which is better, Ornith-1.0-397B or Qwen3.6 Plus?

Which is better for coding, Ornith-1.0-397B or Qwen3.6 Plus?

Which is better for agentic tasks, Ornith-1.0-397B or Qwen3.6 Plus?

Which costs less, Ornith-1.0-397B or Qwen3.6 Plus?

Which has the larger context window, Ornith-1.0-397B or Qwen3.6 Plus?

Related comparisons

Watch Ornith-1.0-397B vs Qwen3.6 Plus