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ModelCap

Qwen3.8 Flash

Official publisher releaseRestricted license

Qwen·#89 of 351 on the current board·cheaper than #88 Qwen3 VL 235B A22B Instruct

Qwen3.8 Flash is a language model from Qwen. It ranks #89 of 351 on ModelCap's current board, with an Index score of 57.1, modeled from its measured predecessor. Its score range of 44.9–69.2 spans positions #40–#133. It is listed at $0.15 per million input tokens and $0.47 per million output tokens from one provider. It reads up to 1M tokens of context, and its weights are downloadable under a use-restricted licence.

Figures as of 18 Oct 2026, 03:08 UTC · download the public dataset · methodology

ModelCap Index · Current board
57.1#89
Modeled from its measured predecessor · range 44.9–69.2
Market Gravity
40.4Decreased by 0.7
Secondary market signal
Input
$0.15
per 1M tokens
Output
$0.47
per 1M tokens
Context
1M
tokens
Providers
1
2 endpoints

Providers

Uptime measured over the last 30 minutes
ProviderInputOutputContextQuantUptime
Alibabaus-east-1Cheapest$0.15$0.471M—100.0%
Alibaba$0.15$0.471M—100.0%

Reported evaluation leads (13)

Not independent measurement

Structured rows reported in this exact model repository at the pinned revision below. They are the publisher talking about itself: never measured evidence, never a score input on their own. Rows marked as used were laddered against independently measured peers inside the launch-card channel of this model's modeled placement, with the replay-measured optimism haircut applied; the others played no part.

Dataset / taskMetricValueRevisionProvenance
agents-last-exam/agents-last-exam
overall-pass-rate
—24.3
Unpinned
not published
Reported
Not used in launch estimate
agents-last-exam/agents-last-exam
overall-score
—51.2
Unpinned
not published
Reported
Not used in launch estimate
cais/hle
hle
—35.9
Unpinned
not published
Reported
Used in launch estimate
claw-eval/Claw-Eval
multimodal
—64.4
Unpinned
not published
Reported
Not used in launch estimate
datacurve/deep-swe
deep_swe
—58.7
Unpinned
not published
Reported
Not used in launch estimate
hkust-nlp/Toolathlon
toolathlon_verified
—73.5
Unpinned
not published
Reported
Not used in launch estimate
Idavidrein/gpqa
diamond
—91.7
Unpinned
not published
Reported
Not used in launch estimate
llamaindex/ExtractBench
mean
—89.88
Unpinned
not published
Reported
Not used in launch estimate
llamaindex/ExtractBench
short
—94.82
Unpinned
not published
Reported
Not used in launch estimate
llamaindex/ExtractBench
medium
—87.81
Unpinned
not published
Reported
Not used in launch estimate
llamaindex/ExtractBench
long
—37.74
Unpinned
not published
Reported
Not used in launch estimate
ScaleAI/SWE-bench_Pro
SWE_Bench_Pro
—62.5
Unpinned
not published
Reported
Used in launch estimate
SWE-bench/SWE-bench_Multilingual
swe_bench_multilingual_%_resolved
—81
Unpinned
not published
Reported
Used in launch estimate

Other versions (3)

ModelCap Index · Current board

Methodology
57.1
Modeled from its measured predecessor
Current board
#89 of 351
Score range
44.9–69.2
Rank range
#40–#133
Technical details
Public rank basis
Modeled · succession (architecture)
Evidence label
Modeled · succession · publisher-corpus-prior over 213 held-out anchors (16%); measured predecessor qwen/qwen3.5-flash-02-23 less the succession penalty (63%); launch card against 3 resolved peers on 10 rows (21%); exceeds every named peer on 9 of 10 rows; no cross-lab optimism probe available; shrunk 1.2 toward the measured corpus
Index support
40.0% · limited
Identity binding
Exact catalogue product · qwen/qwen/qwen3.8-flash · aggregates disclosed benchmark configurations · endpoint configuration not claimed · artifact metadata Qwen/Qwen3.8-Flash-Next@de4b8e4d43b917e7706784d8bb445c9af86a3540 (not the evaluation revision)
Index observations used
0
Qualified Index evidence point
57.1
How this position was produced · fused launch placement

No general-family board lists this model yet. Its point estimate is the precision-weighted mean of every channel that spoke for it; each channel’s share is the weight it carried. Independent measurements replace this placement as boards list the model.

Fused estimate
57.1 ± 9.5
Independent share
0%
Shrink toward corpus
-1.2
Peer ceiling share
90%
Optimism haircut
None applied
Method
precision-weighted-v1
Channels fused into this model’s launch placement
ChannelEstimateShare
Publisher corpus prior · not independent
publisher-corpus-prior over 213 held-out anchors
50.9 ± 23.516%
Family succession · not independent
measured predecessor qwen/qwen3.5-flash-02-23 less the succession penalty
49.2 ± 12.063%
Launch card against resolved peers · not independent
launch card against 3 resolved peers on 10 rows
85.3 ± 20.721%
  • · Launch card row deepswe-1-1: claims above every resolved peer
  • · Launch card row erqa: claims above every resolved peer
  • · Launch card row gpqa-diamond: claims above every resolved peer
  • · Launch card row hle: inside the resolved peer range
  • · Launch card row ifbench: claims above every resolved peer
  • · Launch card row livecodebench-v-6: claims above every resolved peer
  • · Launch card row nl-2-repo: claims above every resolved peer
  • · Launch card row swe-bench-multilingual: claims above every resolved peer
  • · Launch card row swe-bench-pro: claims above every resolved peer
  • · Launch card row toolathlon-verified: claims above every resolved peer
Bayesian Evidence Score · measured evidence input only

BES normalizes admitted public benchmark evidence for measured Index rows. Its legacy score and observables prior do not define the public language rank.

Observed capability
—
Evidence status
No admitted measured evidence
General preference
—
Coding
—
Agents & tools
—
Reasoning
—
Evidence breadth
0%
Evidence coverage
0%
Market and catalogue signals · secondary, never the language Index rank
Usage (OpenRouter popularity)
36.7
Liquidity (providers × uptime)
34.5
Open reach (HF downloads)
—
Surface (context / tools / modalities)
100.0
Freshness
81.9
  • · OpenRouter popularity #40
  • · 1 live provider
  • · Catalogue: context 1000000, reasoning, tools, modalities Text/Image/Video
  • · First seen 2026-08-26

These adoption and deployment observations remain context only. They do not change this model's ModelCap Index score or rank.

The bounded 0–100 capability score blends each source’s competitive placement with its published achievement, then combines capability families. Evidence breadth adds a modest uncertainty adjustment; price and popularity are not part of benchmark-led rank.

Experimental capability estimate

Estimate policy
68.3
54.4–82.2 uncertainty interval
Excluded from rank
Confidence
78%
Training support
222 models · 127 lineages
Out-of-domain check
in domain
Feature coverage
100%
Lineage-held-out error
8.6 MAE

Experimental estimate. This layer predicts from admitted evidence and safe metadata only. It never enters ModelCap Score or rank.

Deployment readiness

Metadata index
68.0
partial · 76% metadata coverage
Not capability
Artifact reproducibility
85.0
Access & legal clarity
92.5
Deployability
80.0
Evaluation provenance
0.0

Not yet published: the base model it derives from, admitted benchmark results, results across several capability areas, results from more than one source, a confident match to its benchmark entries, pinned evaluation dataset versions.

A metadata completeness and deployability index—not a safety certification, quality grade, or production-readiness claim.

Market activity

Venue coverage
Market Gravity
40.4
OpenRouter weekly popularity
#40 of 341

Market Gravity uses OpenRouter’s full-catalogue popularity order. Sparse Vercel top-ten observations appear only when published and do not affect the score.

Arena preference

No matched Arena rating

This model is visible because it is available in the live catalogue, but it has no trustworthy community result yet. ModelCap does not infer a quality score from price, features, or market activity.

Market Gravity breakdown

Usage55%
36.7

OpenRouter weekly popularity across the full model catalogue.

Liquidity25%
34.5

Independent providers versus the model's open or closed cohort, weighted by uptime.

Open reach15%
50.0

Hugging Face 30-day downloads for open models; neutral for closed models.

Freshness5%
81.9

Time since first public availability, on a six-month half-life.

Specification

Model ID
qwen/qwen3.8-flash
Context window
1M tokens
Declared output cap
131K tokens

OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. OpenRouter metadata

Inputs
Text, Image, Video
Outputs
Text
Tokenizer
Qwen
Cached input tokens
$0.016 / 1M
First seen on OpenRouter
26 Aug 2026

Capabilities

  • Supported: Reasoning
  • Supported: Tool use
  • Supported: Structured output
  • Supported: Response format
  • Not supported: Moderated

Weights & access

Restricted license. Downloadable weights use a model-specific or use-restricted license. Review the linked license before use, redistribution, or commercial deployment.

Access
Restricted license
Pinned revision
de4b8e4d43b9
Parameters
180.0B
Architecture
Qwen4ExpForConditionalGeneration
Model type
qwen4_exp
Hugging Face downloads (30d)
2.5M
Downloads (all time)
3.2M
Likes
6K
Repository updated
27 Aug 2026, 05:03 UTC

Benchmark leaderboards featuring Qwen3.8 Flash

All leaderboards
Public benchmark boards on which Qwen3.8 Flash has a published result
LeaderboardScoreSource rankConfigurationPublished
Artificial Analysis Intelligence IndexArtificial Analysis39.8#45 of 134Reasoning7 Oct 2026
Terminal-Bench 2.1 (Artificial Analysis run)Artificial Analysis86.1%#13 of 128Reasoning1 Oct 2026
Humanity's Last Exam (Artificial Analysis run)Artificial Analysis38.0%#56 of 267Reasoning5 Sept 2026

Alternatives to Qwen3.8 Flash, by the numbers

Ranked neighbours

Models within 3 places of #89 on the ModelCap Index.

Cheaper at a similar or higher Index

Index score within 3 points of, or above, this model's, with a lower listed blended price (3:1 input:output).

Other ranked Qwen models

The same publisher's other current models with a public Index position.

Qwen3.8 Flash: common questions

How does Qwen3.8 Flash rank among AI models?

Qwen3.8 Flash holds ModelCap Index position #89 of 351 ranked language models as of 18 October 2026, with an Index score of 57.1 (interval 44.9–69.2); evidence: modeled · succession. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.

How much does Qwen3.8 Flash cost per 1M tokens?

Qwen3.8 Flash is listed at $0.15 per 1M input tokens and $0.47 per 1M output tokens as of 18 October 2026. Prices come from the OpenRouter catalogue and re-observe on every refresh. For 1,000 requests using 2,000 input and 500 output tokens each, the listed rates imply $0.535 total (2M input + 0.5M output). This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the chosen endpoint's rate and limits before budgeting.

What is the context window of Qwen3.8 Flash?

Qwen3.8 Flash has a published context window of 1M tokens (1,000,000). The snapshot lists a 131,072 token catalogue-declared route output cap. OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. The providers table lists each endpoint's context limit.

Is Qwen3.8 Flash open-weight?

Restricted license (qwen-community-1.0). Downloadable weights use a model-specific or use-restricted license. Review the linked license before use, redistribution, or commercial deployment. The repository is Qwen/Qwen3.8-Flash-Next on Hugging Face.

Which API providers serve Qwen3.8 Flash?

One provider serves Qwen3.8 Flash through OpenRouter as of 18 October 2026: Alibaba. Each provider's price, context limit, quantization and measured uptime are in the providers table above.

Which benchmarks has Qwen3.8 Flash been evaluated on?

Qwen3.8 Flash has published results on 3 public boards tracked by ModelCap as of 18 October 2026: AA Intelligence Index 39.8 (#45 of 134), AA Terminal-Bench 2.1 86.1% (#13 of 128) and AA Humanity's Last Exam 38.0% (#56 of 267). Each board page ranks every tracked model on that benchmark. The ModelCap Index scores the results its methodology admits, with published uncertainty, and shows reference boards without scoring them.

When was Qwen3.8 Flash released?

Qwen3.8 Flash first appeared in the catalogue on 26 Aug 2026. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.