Qwen3.8 Flash
Qwen3.8 Flash is a multimodal reasoning model from Alibaba. It is suited for coding assistance, agentic workflows, visual understanding, document and codebase analysis, desktop interaction, chart analysis, and long-video analysis.
Updated 3 h ago · first seen 11 Sept 2026
model_01M294WVPZ414HS0N3YM40G6EE
Overview
Identity
- Canonical model
- Yesidentity confidence: mediumOne row per real model release. Artifacts (checkpoints, quantisations, conversions) and folded evaluation variants point here.
- Official checkpoints
- official_checkpoints = hf_repo identifiers carried by the model itself; artifacts are separate entities pointing here through canonical_id.
- Artifacts
- 2 quantizations0 official · 2 third-partySeparate entities (checkpoint · quantization · conversion · packaging) pointing to this model through canonical_id.
- Provider deployments
- 2
- API aliases
- qwen/qwen3.8-flashqwen3-8-flash-nextIdentifiers under which providers and evaluators refer to this model.
- Folded evaluation variants
- 0Effort / thinking variants (…-high, …-non-reasoning) are result configurations of this model, not separate models. Their old URLs redirect here.
Openness
Open weights— weights downloadable; 7 dimensions unknown.
Weights downloadable under a permissive or Creative Commons licence allowing commercial use; code or data may be missing.
Weights
Yes
Inference code
—
Training code
—
Training data
—
Dataset
—
Commercial use
—
Redistribution
—
Derivatives
—
dimensions marked null are unknown, not false
Key facts
- Release date
Source:OpenRouter public model & pricing listingT2observed 13 h agomedium
- Openrouter id
Source:OpenRouter public model & pricing listingT2observed 13 h agomedium
Architecture
- Tokenizer
Source:OpenRouter public model & pricing listingT2observed 13 h agomedium
- Hugging Face repo
Source:OpenRouter public model & pricing listingT2observed 13 h agomedium
Capabilities
Modalities
- Modalities
- imagetextvideo
- Input
- imagetextvideo
- Output
- text
Capabilities
Tool calling
Yes
OpenRouter public model & pricing listing · T2
Structured output
Yes
OpenRouter public model & pricing listing · T2
Reasoning
Yes
OpenRouter public model & pricing listing · T2
Vision
Yes
OpenRouter public model & pricing listing · T2
Audio
Unavailable
Fine-tuning available
Unavailable
- Context window
Source:OpenRouter public model & pricing listingT2observed 10 h agomedium
- Max output
Source:OpenRouter public model & pricing listingT2observed 13 h agomedium
- Tokenizer
Source:OpenRouter public model & pricing listingT2observed 13 h agomedium
Benchmarks22
Compare with another model →Comparable same task and conditions · Partially comparable same task, conditions differ (effort, temperature, judge) · Not comparable different variant or metric
Current rows only, grouped by benchmark → canonical metric → comparability group (task configuration). Effort variants folded into this model appear as rows of the same group. 22 current rows in total. “vs leader” compares with the current leader of the benchmark's primary group only; other groups are not directly comparable. Comparability rules →
Providers & Pricing2
All offers in the price terminal →USD per 1M tokens as published by each provider; native units (per-request fees, flex/priority tiers) are kept verbatim. Rows are append-only — every price change is kept in the history below. Cost of a workload →
Price history
Output price · USD / 1M tokens 2 providers
- OpenRouter
- Together AI
- Together AIfirst observed $0.4711 Sept 2026
- OpenRouterfirst observed $0.4711 Sept 2026
Input price · USD / 1M tokens 2 providers
- OpenRouter
- Together AI
- Together AIfirst observed $0.1511 Sept 2026
- OpenRouterfirst observed $0.1511 Sept 2026
Lineage
Open in Graph →Versions & Artifacts2
Version history
Context window2 changes
11 Sept 2026→11 Sept 2026→12 Sept 2026current
Max outputfirst observation only
11 Sept 2026current
Opennessfirst observation only
11 Sept 2026current
Each hop is a claim: click a value for its source, tier and observation time. Nothing is overwritten — a new observation closes the previous claim.
Artifacts 2
quantizations 2
- Intel/Qwen3.8-Flash-Next-W4A16-AutoRoundIntel · BF16/F16/I32/I64181.2 GB
- unsloth/Qwen3.8-Flash-Next-GGUFUnsloth · GGUF—
Timeline8
Full timeline →Qwen3.8 Flash scores 86.14% on Terminal-Bench
artificial_analysisQwen3.8 Flash scores 25.25% on Terminal-Bench
artificial_analysisQwen3.8 Flash scores 38.04% on Humanity's Last Exam
artificial_analysisQwen3.8 Flash scores 92.32% on GPQA Diamond
artificial_analysisQwen3.8 Flash scores 39.91 on Artificial Analysis Intelligence Index
artificial_analysisQwen3.8 Flash: context length changed from 256000 to 1000000
Context window256K tokens→1M tokensopenrouter
Change history
Aa median output tokens per secondmetric.aa_median_output_tokens_per_second1
Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →
Provenance
Attributed facts
23
Source tiers
T223
Freshest observation
3 h ago
Conflicts
None
Source documents 6
Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.
Data quality (64/100) measures how well AI Atlas knows this entity — completeness, primary-source ratio, freshness, conflicts — never how good the model is. Methodology →