Qwen3.7 Flash

No linked weights

Qwen·#226 of 504 in the all-versions archive

Qwen3.7 Flash is a language model from Qwen. It ranks #226 of 504 in ModelCap's all-versions archive, with an Index score of 48.7, modeled from its measured predecessor. Its score range of 35.0–62.4 spans positions #127–#315. It is listed at $0.03 per million input tokens and $0.13 per million output tokens from one provider. It reads up to 1M tokens of context, with no downloadable weights linked in the current source data.

Figures as of 6 Nov 2026, 13:52 UTC · download the public dataset · methodology

ModelCap Index · All-versions archive

48.7#226

Modeled from its measured predecessor · range 35.0–62.4

Market Gravity

54.3

Secondary market signal

Superseded by Qwen3.8 Flash. It no longer holds a current-board position; its all-versions archive rank is #226.

Input

$0.03

per 1M tokens

Output

$0.13

per 1M tokens

Context

tokens

Providers

2 endpoints

Providers

Uptime measured over the last 30 minutes

Provider	Input	Output	Context	Quant	Uptime
AlibabaCheapest	$0.03	$0.13	1M	—	100.0%
Alibabaus-east-1	$0.034	$0.15	1M	—	100.0%

Other versions (3)

ModelCap Index · All-versions archive

Methodology

48.7

Modeled from its measured predecessor

All-versions archive

#226 of 504

Score range: 35.0–62.4
Rank range: #127–#315

Technical details

Public rank basis: Modeled · succession (architecture)
Evidence label: Modeled · succession · publisher-corpus-prior over 210 held-out anchors (20%); opens from measured predecessor qwen/qwen3.5-flash-02-23 (80%); shrunk 0.6 up toward the measured corpus
Index support: 31.8% · limited
Identity binding: Exact catalogue product · qwen/qwen/qwen3.7-flash · aggregates disclosed benchmark configurations · endpoint configuration not claimed
Index observations used: 0
Qualified Index evidence point: 48.7

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: 48.7 ± 10.7
Independent share: 0%
Shrink toward corpus: +0.6
Optimism haircut: None applied
Method: precision-weighted-v1

Channels fused into this model’s launch placement
Channel	Estimate	Share
Publisher corpus prior · not independent publisher-corpus-prior over 210 held-out anchors	51.0 ± 23.8	20%
Family succession · not independent opens from measured predecessor qwen/qwen3.5-flash-02-23	48.1 ± 12.0	80%

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): 35.4
Liquidity (providers × uptime): 95.8
Open reach (HF downloads): —
Surface (context / tools / modalities): 100.0
Freshness: 67.9

· OpenRouter popularity #43
· 1 live provider
· Catalogue: context 1000000, reasoning, tools, modalities Text/Image/Video
· First seen 2026-07-27

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

Estimator abstained

insufficient-artifact-metadata

Feature coverage: 86%
Training support: 220 models · 128 lineages

insufficient-artifact-metadata. This layer predicts from admitted evidence and safe metadata only. It never enters ModelCap Score or rank.

Deployment readiness

Metadata index

30.1

limited · 38% metadata coverage

Not capability

Artifact reproducibility: 0.0
Access & legal clarity: 30.3
Deployability: 80.0
Evaluation provenance: 0.0

Not yet published: a pinned repository revision, the architecture and model type, a parameter count, safetensors weight metadata, the base model it derives from, a declared licence, a link to the licence terms, 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: 54.3
OpenRouter weekly popularity: #43 of 339

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%: 35.4
Liquidity25%: 95.8
Open reach15%: 50.0
Freshness5%: 67.9

Specification

Model ID: qwen/qwen3.7-flash
Context window: 1M tokens
Declared output cap: 66K 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: $0.0060 / 1M
First seen on OpenRouter: 27 Jul 2026

Capabilities

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

Qwen3.7 Flash: common questions

How does Qwen3.7 Flash rank among AI models?

Qwen3.7 Flash is a superseded version and is not on the current board as of 6 November 2026. Its archive position, where one exists, is shown on the page; the newer version carries the current rank.

How much does Qwen3.7 Flash cost per 1M tokens?

Qwen3.7 Flash is listed at $0.03 per 1M input tokens and $0.13 per 1M output tokens as of 6 November 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 $0.125 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 Qwen3.7 Flash?

Qwen3.7 Flash has a published context window of 1M tokens (1,000,000). The snapshot lists a 65,536 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 Qwen3.7 Flash open-weight?

No linked weights. No downloadable model weights are linked in the current source data. This does not identify every API or chat product that offers the model.

Which API providers serve Qwen3.7 Flash?

One provider serves Qwen3.7 Flash through OpenRouter as of 6 November 2026: Alibaba. Each provider's price, context limit, quantization and measured uptime are in the providers table above.

When was Qwen3.7 Flash released?

Qwen3.7 Flash first appeared in the catalogue on 27 Jul 2026. It has since been superseded by Qwen3.8 Flash. Rank and price movements since then are recorded on the site's changes feed.