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ModelCap

Qwen3.6 35B A3B

Official publisher releaseOpen weights6.9d #104 → #106

Qwen·#106 of 352 on the current board·cheaper than #96 Qwen3 VL 235B A22B Instruct

Qwen3.6 35B A3B is a language model from Qwen. It ranks #106 of 352 on ModelCap's current board, with an Index score of 53.7, modeled from the publisher's launch results against measured models. Its score range of 43.5–63.9 spans positions #65–#150. It is listed at $0.10 per million input tokens and $0.90 per million output tokens across 11 providers. It reads up to 262K tokens of context, and its weights are openly downloadable.

Figures as of 6 Nov 2026, 20:32 UTC · download the public dataset · methodology

ModelCap Index · Current board
53.7#106
Modeled from the publisher's launch results against measured models · range 43.5–63.9
Market Gravity
53.8Increased by 0.5
Secondary market signal
Input
$0.10
per 1M tokens
Output
$0.90
per 1M tokens
Context
262K
tokens
Providers
11
endpoints

Providers

Uptime measured over the last 30 minutes
ProviderInputOutputContextQuantUptime
PrimeIntellectfp8Cheapest$0.012$0.115262Kfp8100.0%
Darkbloomfp4$0.05$0.70262Kfp4100.0%
CoreWeavefp8$0.10$0.89262Kfp8100.0%
AkashMLfp8$0.10$0.90262Kfp8100.0%
Parasailfp8$0.10$0.90262Kfp8100.0%
DeepInfrafp8$0.10$0.95262Kfp8100.0%
DekaLLM$0.10$1.00262K—100.0%
Venicefp8$0.10$1.00256Kfp8100.0%
AtlasCloudfp8$0.25$1.25262Kfp8100.0%
Phala$0.20$1.27262K—100.0%
SiliconFlowfp8$0.24$1.80262Kfp8100.0%

Hugging Face Inference Providers

Exact repository identity

Provider economics and telemetry published by the Hugging Face Router. These are operational signals, not benchmark results.

ProviderInputOutputContextTTFTThroughputFeatures
deepinfra
live
$0.10$0.95262K195 ms149.2 tok/stools · structured
featherless-ai
live
——————

Reported evaluation leads (26)

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
cais/hle
hle
—21.4
Unpinned
not published
Reported
Used in launch estimate
harborframework/terminal-bench-2.0
terminalbench_2
—51.5
Unpinned
not published
Reported
Used in launch estimate
Idavidrein/gpqa
diamond
—86
Unpinned
not published
Reported
Used in launch estimate
llamaindex/ExtractBench
mean
—88.11
Unpinned
not published
Reported
Not used in launch estimate
llamaindex/ExtractBench
short
—92.86
Unpinned
not published
Reported
Not used in launch estimate
llamaindex/ExtractBench
medium
—86.37
Unpinned
not published
Reported
Not used in launch estimate
llamaindex/ExtractBench
long
—36.9
Unpinned
not published
Reported
Not used in launch estimate
llamaindex/ParseBench
mean
—44.1
Unpinned
not published
Reported
Not used in launch estimate
llamaindex/ParseBench
text_content
—90.7
Unpinned
not published
Reported
Not used in launch estimate
llamaindex/ParseBench
text_formatting
—58.3
Unpinned
not published
Reported
Not used in launch estimate
llamaindex/ParseBench
layout
—47.4
Unpinned
not published
Reported
Not used in launch estimate
llamaindex/ParseBench
chart
—5.1
Unpinned
not published
Reported
Not used in launch estimate
llamaindex/ParseBench
table
—19.1
Unpinned
not published
Reported
Not used in launch estimate
MathArena/aime_2026
MathArena/aime_2026
—92.7
Unpinned
not published
Reported
Not used in launch estimate
MathArena/hmmt_feb_2026
MathArena/hmmt_feb_2026
—83.6
Unpinned
not published
Reported
Used in launch estimate
MBZUAI/longshot-bench
overall
—31.86
Unpinned
not published
Reported
Not used in launch estimate
MBZUAI/longshot-bench
core_perception
—23.53
Unpinned
not published
Reported
Not used in launch estimate
MBZUAI/longshot-bench
reasoning
—37.54
Unpinned
not published
Reported
Not used in launch estimate
MBZUAI/longshot-bench
information
—28.99
Unpinned
not published
Reported
Not used in launch estimate
MBZUAI/longshot-bench
multimodal
—37.38
Unpinned
not published
Reported
Not used in launch estimate

Showing 20 of 26 rows.

Other versions (1)

ModelCap Index · Current board

Methodology
53.7
Modeled from the publisher's launch results against measured models
Current board
#106 of 352
Score range
43.5–63.9
Rank range
#65–#150
Technical details
Public rank basis
Modeled · peer benchmarks (architecture)
Evidence label
Modeled · peer benchmarks · publisher-corpus-prior over 210 held-out anchors (11%); opens above measured predecessor qwen/qwen3.5-35b-a3b on same-family ordering evidence (44%); launch card against 4 resolved peers on 10 rows (45%); exceeds every named peer on 2 of 10 rows; optimism haircut 0 from cross-lab-probe; shrunk 0.3 toward the measured corpus
Index support
40.0% · limited
Identity binding
Exact catalogue product · qwen/qwen/qwen3.6-35b-a3b · aggregates disclosed benchmark configurations · endpoint configuration not claimed · artifact metadata Qwen/Qwen3.6-35B-A3B@995ad96eacd98c81ed38be0c5b274b04031597b0 (not the evaluation revision)
Index observations used
0
Qualified Index evidence point
53.7
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
53.7 ± 8.0
Independent share
0%
Shrink toward corpus
-0.3
Peer ceiling share
20%
Optimism haircut
None required · cross lab probe, 5 probes
Method
precision-weighted-v1
Channels fused into this model’s launch placement
ChannelEstimateShare
Publisher corpus prior · not independent
publisher-corpus-prior over 210 held-out anchors
51.0 ± 23.811%
Family succession · not independent
opens above measured predecessor qwen/qwen3.5-35b-a3b on same-family ordering evidence
51.0 ± 12.044%
Launch card against resolved peers · not independent
launch card against 4 resolved peers on 10 rows
57.1 ± 12.045%
  • · Launch card row gpqa: claims above every resolved peer
  • · Launch card row hle: inside the resolved peer range
  • · Launch card row hmmt-2026: inside the resolved peer range
  • · Launch card row mmlu-pro: inside the resolved peer range
  • · Launch card row mmmu-pro: inside the resolved peer range
  • · Launch card row mmmu: inside the resolved peer range
  • · Launch card row swe-bench-multilingual: inside the resolved peer range
  • · Launch card row swe-bench-pro: inside the resolved peer range
  • · Launch card row swe-bench-verified: inside the resolved peer range
  • · Launch card row terminal-bench-2-0: 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)
29.7
Liquidity (providers × uptime)
89.3
Open reach (HF downloads)
85.0
Surface (context / tools / modalities)
90.3
Freshness
47.8
  • · OpenRouter popularity #60
  • · 11 live providers
  • · HF 30d downloads 4388118
  • · Catalogue: context 262144, reasoning, tools, modalities Text/Image/Video
  • · First seen 2026-04-27

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
54.8
41.1–68.4 uncertainty interval
Excluded from rank
Confidence
80%
Training support
220 models · 128 lineages
Out-of-domain check
in domain
Feature coverage
100%
Lineage-held-out error
8.3 MAE

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

Deployment readiness

Metadata index
75.1
strong · 76% metadata coverage
Not capability
Artifact reproducibility
85.0
Access & legal clarity
100.0
Deployability
98.8
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
53.8
OpenRouter weekly popularity
#60 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%
29.7

OpenRouter weekly popularity across the full model catalogue.

Liquidity25%
89.3

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

Open reach15%
85.0

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

Freshness5%
47.8

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

Specification

Model ID
qwen/qwen3.6-35b-a3b
Context window
262K tokens
Declared output cap
236K 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
$0.025 / 1M
First seen on OpenRouter
27 Apr 2026

Capabilities

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

Weights & access

Open weights. Downloadable weights are published under an OSI or free-culture license in the current repository metadata. This describes weight availability, not whether the full training stack qualifies as Open Source AI.

Access
Open weights
Licence
apache-2.0
Pinned revision
995ad96eacd9
Parameters
36.0B
Architecture
Qwen3_5MoeForConditionalGeneration
Model type
qwen3_5_moe
Hugging Face downloads (30d)
4.4M
Downloads (all time)
34.9M
Likes
3K
Repository updated
24 Apr 2026, 02:53 UTC

Alternatives to Qwen3.6 35B A3B, by the numbers

Ranked neighbours

Models within 3 places of #106 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.

Qwen3.6 35B A3B: common questions

How does Qwen3.6 35B A3B rank among AI models?

Qwen3.6 35B A3B holds ModelCap Index position #106 of 352 ranked language models as of 6 November 2026, with an Index score of 53.7 (interval 43.5–63.9); evidence: modeled · peer benchmarks. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.

How much does Qwen3.6 35B A3B cost per 1M tokens?

Qwen3.6 35B A3B is listed at $0.10 per 1M input tokens and $0.90 per 1M output tokens as of 6 November 2026; the lowest output price among 11 providers is $0.115 on PrimeIntellect. 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 $0.65 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 Qwen3.6 35B A3B?

Qwen3.6 35B A3B has a published context window of 262K tokens (262,144). The snapshot lists a 235,929 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 Qwen3.6 35B A3B open-weight?

Open weights (apache-2.0). Downloadable weights are published under an OSI or free-culture license in the current repository metadata. This describes weight availability, not whether the full training stack qualifies as Open Source AI. The repository is Qwen/Qwen3.6-35B-A3B on Hugging Face.

Which API providers serve Qwen3.6 35B A3B?

11 providers serve Qwen3.6 35B A3B through OpenRouter as of 6 November 2026: PrimeIntellect, Darkbloom, CoreWeave, AkashML, Parasail and DeepInfra and 5 more. Each provider's price, context limit, quantization and measured uptime are in the providers table above.

Which benchmarks has Qwen3.6 35B A3B been evaluated on?

Qwen3.6 35B A3B's Index position rests on the evidence listed on this page; it has no result on the public boards ModelCap tracks as separate leaderboards as of 6 November 2026. The evidence panel names each source and its publication date.

When was Qwen3.6 35B A3B released?

Qwen3.6 35B A3B first appeared in the catalogue on 27 Apr 2026. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.