NaiveAILanguage modelOpen weights
Naive-N0.5-Flash
Naive-N0.5-Flash has no overall index value yet because there are too few independent benchmark results.
PopularityRank 235 of 875
42out of 100same as last month
Summary
Naive-N0.5-Flash combines sliding-window attention with DeepSeek sparse attention for a 1M-token context window. The open MoE checkpoint activates 15.5 of its 309 billion parameters per token.
NaiveAI releases the weights under MIT. Its model card documents FP8 deployment on NVIDIA hardware.
All benchmark results
Every published result with its source, test setup and comparison models.
Show all 13 published benchmark results
Page 1 of 2
Measurements without matching peer values
These measurements have no matching peer values under the same test conditions. Their original values and sources remain available here.
MLE-bench-30 (Show measurement, test conditions, and source)
- Source value
- 73.7
- Score
- 73.7
- Metric
- MLE-bench-30
- Unit
- %
- Category
- source-specific
- Direction
- Higher is better
- Source type
- vendor-reported
- Evaluator
- Provider model card
- Status
- active
- Retrieved at
- 2026-10-04
- Methodology
- Vendor-reported result. Official image-only card, visually inspected. Default Claude Code 2.1.207, 1M context, tool environment; proprietary agent/R&D harnesses.
- Context
- Source-specific observation; it is not a shared comparison cohort.
DeepSWE v1.1 (Show measurement, test conditions, and source)
- Source value
- 67.8
- Score
- 67.8
- Metric
- DeepSWE v1.1 reported score
- Unit
- No unit provided
- Category
- source-specific
- Direction
- Higher is better
- Source type
- vendor-reported
- Evaluator
- Provider model card
- Status
- active
- Retrieved at
- 2026-10-04
- Methodology
- Vendor-reported result. Official image-only card, visually inspected. Default Claude Code 2.1.207, 1M context, tool environment; proprietary agent/R&D harnesses.
- Context
- Source-specific observation; it is not a shared comparison cohort. The source table does not state a unit or scale for this numeric score.
Agents Last Exam (Show measurement, test conditions, and source)
- Source value
- 32.4
- Score
- 32.4
- Metric
- Agents Last Exam reported score
- Unit
- No unit provided
- Category
- source-specific
- Direction
- Higher is better
- Source type
- vendor-reported
- Evaluator
- Provider model card
- Status
- active
- Retrieved at
- 2026-10-04
- Methodology
- Vendor-reported result. Official image-only card, visually inspected. Default Claude Code 2.1.207, 1M context, tool environment; proprietary agent/R&D harnesses.
- Context
- Source-specific observation; it is not a shared comparison cohort. The source table does not state a unit or scale for this numeric score.
TerminalBench 2.1 (Show measurement, test conditions, and source)
- Source value
- 86.7
- Score
- 86.7
- Metric
- TerminalBench 2.1 reported score
- Unit
- No unit provided
- Category
- source-specific
- Direction
- Higher is better
- Source type
- vendor-reported
- Evaluator
- Provider model card
- Status
- active
- Retrieved at
- 2026-10-04
- Methodology
- Vendor-reported result. Official image-only card, visually inspected. Default Claude Code 2.1.207, 1M context, tool environment; proprietary agent/R&D harnesses.
- Context
- Source-specific observation; it is not a shared comparison cohort. The source table does not state a unit or scale for this numeric score.
SWE-Bench Pro (Show measurement, test conditions, and source)
- Source value
- 73.6
- Score
- 73.6
- Metric
- SWE-Bench Pro reported score
- Unit
- No unit provided
- Category
- source-specific
- Direction
- Higher is better
- Source type
- vendor-reported
- Evaluator
- Provider model card
- Status
- active
- Retrieved at
- 2026-10-04
- Methodology
- Vendor-reported result. Official image-only card, visually inspected. Default Claude Code 2.1.207, 1M context, tool environment; proprietary agent/R&D harnesses.
- Context
- Source-specific observation; it is not a shared comparison cohort. The source table does not state a unit or scale for this numeric score.
ProgramBench (Show measurement, test conditions, and source)
- Source value
- 17.5
- Score
- 17.5
- Metric
- ProgramBench reported score
- Unit
- No unit provided
- Category
- source-specific
- Direction
- Higher is better
- Source type
- vendor-reported
- Evaluator
- Provider model card
- Status
- active
- Retrieved at
- 2026-10-04
- Methodology
- Vendor-reported result. Official image-only card, visually inspected. Default Claude Code 2.1.207, 1M context, tool environment; proprietary agent/R&D harnesses.
- Context
- Source-specific observation; it is not a shared comparison cohort. The source table does not state a unit or scale for this numeric score.
NL2Repo (Show measurement, test conditions, and source)
- Source value
- 71.9
- Score
- 71.9
- Metric
- NL2Repo reported score
- Unit
- No unit provided
- Category
- source-specific
- Direction
- Higher is better
- Source type
- vendor-reported
- Evaluator
- Provider model card
- Status
- active
- Retrieved at
- 2026-10-04
- Methodology
- Vendor-reported result. Official image-only card, visually inspected. Default Claude Code 2.1.207, 1M context, tool environment; proprietary agent/R&D harnesses.
- Context
- Source-specific observation; it is not a shared comparison cohort. The source table does not state a unit or scale for this numeric score.
FrontierSWE v1 (Show measurement, test conditions, and source)
- Source value
- 78.2
- Score
- 78.2
- Metric
- FrontierSWE v1 reported score
- Unit
- No unit provided
- Category
- source-specific
- Direction
- Higher is better
- Source type
- vendor-reported
- Evaluator
- Provider model card
- Status
- active
- Retrieved at
- 2026-10-04
- Methodology
- Vendor-reported result. Official image-only card, visually inspected. Default Claude Code 2.1.207, 1M context, tool environment; proprietary agent/R&D harnesses.
- Context
- Source-specific observation; it is not a shared comparison cohort. The source table does not state a unit or scale for this numeric score.
PostTrainBench (Show measurement, test conditions, and source)
- Source value
- 37.5
- Score
- 37.5
- Metric
- PostTrainBench reported score
- Unit
- No unit provided
- Category
- source-specific
- Direction
- Higher is better
- Source type
- vendor-reported
- Evaluator
- Provider model card
- Status
- active
- Retrieved at
- 2026-10-04
- Methodology
- Vendor-reported result. Official image-only card, visually inspected. Default Claude Code 2.1.207, 1M context, tool environment; proprietary agent/R&D harnesses.
- Context
- Source-specific observation; it is not a shared comparison cohort. The source table does not state a unit or scale for this numeric score.
PaperBench (Show measurement, test conditions, and source)
- Source value
- 63.2
- Score
- 63.2
- Metric
- PaperBench reported score
- Unit
- No unit provided
- Category
- source-specific
- Direction
- Higher is better
- Source type
- vendor-reported
- Evaluator
- Provider model card
- Status
- active
- Retrieved at
- 2026-10-04
- Methodology
- Vendor-reported result. Official image-only card, visually inspected. Default Claude Code 2.1.207, 1M context, tool environment; proprietary agent/R&D harnesses.
- Context
- Source-specific observation; it is not a shared comparison cohort. The source table does not state a unit or scale for this numeric score.
SOL-ExecBench meanSOL (Show measurement, test conditions, and source)
- Source value
- 72.81
- Score
- 72.81
- Metric
- SOL-ExecBench meanSOL reported score
- Unit
- No unit provided
- Category
- source-specific
- Direction
- Higher is better
- Source type
- vendor-reported
- Evaluator
- Provider model card
- Status
- active
- Retrieved at
- 2026-10-04
- Methodology
- Vendor-reported result. Official image-only card, visually inspected. Default Claude Code 2.1.207, 1M context, tool environment; proprietary agent/R&D harnesses.
- Context
- Source-specific observation; it is not a shared comparison cohort. The source table does not state a unit or scale for this numeric score.
NanoChat AutoResearch validation BPB (Show measurement, test conditions, and source)
- Source value
- 0.9051
- Score
- 0.9051
- Metric
- NanoChat AutoResearch validation BPB reported score
- Unit
- No unit provided
- Category
- source-specific
- Direction
- Lower is better
- Source type
- vendor-reported
- Evaluator
- Provider model card
- Status
- active
- Retrieved at
- 2026-10-04
- Methodology
- Vendor-reported result. Official image-only card, visually inspected. Default Claude Code 2.1.207, 1M context, tool environment; proprietary agent/R&D harnesses.
- Context
- Source-specific observation; it is not a shared comparison cohort. The source table does not state a unit or scale for this numeric score.
Page 1 of 2
Popularity compared
How often the model is searched for, used and mentioned, compared with every model of its category.
Popularity index
The 100 most popular models of this category, 0 to 100, higher is more popular
20 of 101 models
Gemini 4 Argon, Google DeepMind: 92
GPT-6 Astra, OpenAI: 78
Claude Haiku 5.5, Anthropic: 77
Qwen3.5 4B, Alibaba: 76
GPT-5, OpenAI: 73
GPT-6 Sol, OpenAI: 72
Qwen3.5 0.8B, Alibaba: 72
Qwen3.5 2B, Alibaba: 71
Qwen 3.8 27B, Alibaba: 70
Claude Opus 5.5, Anthropic: 70
DeepSeek V4.1 Flash 1017, DeepSeek: 68
Qwen 3.8 Max 0902, Alibaba: 68
Kimi K3, Moonshot AI: 68
DeepSeek-V4-Flash, DeepSeek: 65
GPT-5.6 Terra, OpenAI: 64
Claude Sonnet 5, Anthropic: 63
DiffusionGemma 26B A4B IT, Google: 63
Claude Opus 5, Anthropic: 62
Qwen 3.8 Flash, Alibaba: 62
Naive-N0.5-Flash, NaiveAI: 42
As of November 2026 · Source: gradually.ai popularity index
Over time
Weekly values from October 18, 2026 to November 5, 2026
Naive-N0.5-FlashGLM-4.5VLlama 3.2 3BMing-flash-omni-2.0Ornith 1.0 9B
All specifications
Architecture
Input and output
Watermarking and provenance
AI watermarking refers to invisible signals embedded in the output. Visible marks and provenance metadata are listed separately. Unknown means there is insufficient evidence for that particular field.
- AI watermarking
- Unknown
- no source
- Watermarking technique
- Not known
- no source
Licence and access
API
Frequently asked questions about Naive-N0.5-Flash
Can I run Naive-N0.5-Flash locally?
Yes, the weights are open. With 309B parameters it needs a lot of memory, more a server than a laptop.
Stated by NaiveAI
- Open weights
- yes
- License
- MIT
- Parameters
- 309B
- active per token
- 15.5B
Sources and data date
Benchmark sources at a glance
Which independent evaluators tested this model. This is coverage, not a quality ranking.
No active result from the reviewed external evaluators can currently be attributed to this model. Other source evidence remains available below.
Without vendor claims and historical or disputed results; those stay labelled in the single values.
| Type | Evidence and data date |
|---|---|
| Research status | Research date October 4, 2026. 2 source URLs checked. This documents the inspected sources, not an exhaustive inventory of every publication. |
| Additional source | Naive-N0.5-Flash model card (retrieved October 3, 2026; October 4, 2026) · Naive-N0.5-Flash model card · Editorial description reviewed October 4, 2026 |
| Additional source | NaiveAI research page (retrieved October 22, 2026) |
| Additional source | OpenRouter: Popularity index (derived), CC BY 4.0 |
| Additional source | Vercel AI Gateway: Popularity index (derived), CC BY 4.0 |
| Additional source | Ollama: cumulative downloads for the popularity index |
| Additional source | Replicate: cumulative runs for the popularity index |
| Additional source | Google Trending Now: limited feed selection for Germany and the US |
| Additional source | Creative Commons Attribution 4.0 |