Skip to content
ModelCap

Qwen3 32B

Current board #135Arena #209Official publisher releaseOpen weights

Qwen·qwen/qwen3-32b

Qwen3 32B is ModelCap current-board rank #135 with Index 37.6 (Measured), from the ModelCap Index as of 22 Sept 2026, 02:49 UTC.

Qwen3 32B listed OpenRouter input price is $0.08 per 1M tokens and listed output price is $0.28 per 1M tokens, from OpenRouter listed prices as of 22 Sept 2026, 02:49 UTC.

Qwen3 32B has a published context limit of 131K tokens in the ModelCap catalogue as of 22 Sept 2026, 02:49 UTC.

Qwen3 32B has 2 published OpenRouter serving endpoints, from OpenRouter as of 22 Sept 2026, 02:49 UTC.

Qwen3 32B weight access is open weights, from ModelCap classification of published repository metadata as of 22 Sept 2026, 02:49 UTC.

Snapshot facts · download the public dataset · methodology

ModelCap Index · Current board
37.6#135
Measured · 50% support · score interval 31.6–43.6
Evidence as of 13 Sept 2026, 00:00 UTC
Market Gravity
35.6Increased by 0.2
Secondary market signal
Input
$0.08
per 1M tokens
Output
$0.28
per 1M tokens
Context
131K
tokens
Providers
2
endpoints
Gateway spend
latest · Vercel share

Providers

Uptime measured over the last 30 minutes
ProviderInputOutputContextQuantUptime
DeepInfrafp8Cheapest$0.08$0.2841Kfp8100.0%
SiliconFlowfp8$0.14$0.57131Kfp899.84%

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
nscale
live
$0.08$0.2541K701 ms47.9 tok/stools · structured
deepinfra
live
$0.08$0.2841K307 ms26.1 tok/stools · structured
featherless-ai
live

Reported evaluation leads (2)

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. They remain quarantined until dataset revision, harness, configuration and identity pass ModelCap’s independent admission review.

Dataset / taskMetricValueRevisionProvenance
LEXam-Benchmark/LEXam
open_question
40
Unpinned
not published
Reported
Quarantined
LEXam-Benchmark/LEXam
mcq_4_choices
45.3
Unpinned
not published
Reported
Quarantined

Other versions (1)

ModelCap Index · Current board

Methodology
37.6
Measured · 2 public benchmark observations across 2 boards
Current board
#135
Public rank basis
Measured (measured)
Index support
50.2% · moderate
Index interval
31.6–43.6
Rank posterior
Not available
Top 5 / Top 10 probability
Not available / Not available
Posterior as of
Snapshot timestamp unavailable
Evidence as of
13 Sept 2026, 00:00 UTC
Identity binding
Exact catalogue product · qwen/qwen/qwen3-32b · aggregates disclosed benchmark configurations · endpoint configuration not claimed · artifact metadata Qwen/Qwen3-32B@9216db5781bf21249d130ec9da846c4624c16137 (not the evaluation revision)
Index observations used
2
Qualified Index evidence point
37.6
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
37.6
Evidence status
confirmed · 73% mass
General preference
37.3
Coding
39.2
Agents & tools
Reasoning
Evidence breadth
92%
Evidence coverage
50%
Market and catalogue signals · secondary, never the language Index rank
Usage (OpenRouter popularity)
18.4
Liquidity (providers × uptime)
46.6
Open reach (HF downloads)
87.2
Surface (context / tools / modalities)
70.2
Freshness
14.3
  • · OpenRouter popularity #111
  • · 2 live providers
  • · HF 30d downloads 4917936
  • · Catalogue: context 131072, reasoning, tools
  • · First seen 2025-04-28

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

BES evidence selected · measured input only

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.

Deployment readiness

Metadata index
84.0
strong · 94% metadata coverage
Not capability
Artifact reproducibility
85.0
Access & legal clarity
100.0
Deployability
96.2
Evaluation provenance
48.2

Missing: artifactReproducibility.base-lineage, evaluationProvenance.evaluation-dataset-revisions.

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

Market activity

Venue coverage
Market Gravity
35.6
OpenRouter weekly popularity
#111 of 322

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

Status
Ranked
Source
LMArena
Official rank
#209 of 402
Rating
1346.9
95% confidence interval
1337–1356
Votes
4K
Source published at
13 Sept 2026, 00:00 UTC
Category
overall
Identity match confidence
100%

Market Gravity breakdown

Usage55%
18.4

OpenRouter weekly popularity across the full model catalogue.

Liquidity25%
46.6

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

Open reach15%
87.2

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

Freshness5%
14.3

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

Specification

Context window
131K tokens
Max output
16K tokens
Inputs
Text
Outputs
Text
Tokenizer
Qwen3
Cached input tokens
Not offered
First seen on OpenRouter
28 Apr 2025
Knowledge cutoff
2025-03-31

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
9216db5781bf
Parameters
32.8B
Architecture
Qwen3ForCausalLM
Model type
qwen3
Hugging Face downloads (30d)
4.9M
Downloads (all time)
57.6M
Likes
748
Repository
Qwen/Qwen3-32B
Repository updated
26 Jul 2025, 03:45 UTC

Compare Qwen3 32B with

Pick any model

Benchmark leaderboards featuring Qwen3 32B

All leaderboards
Public benchmark boards on which Qwen3 32B has a published result
LeaderboardScoreSource rankConfigurationPublished
Arena coding leaderboardArena (LMArena)14071383–1431#193 of 397Default13 Sept 2026
BFCL V4 function-calling leaderboardUC Berkeley (Gorilla)48.7#24 of 83Function calling12 Apr 2026

Alternatives to Qwen3 32B, by the numbers

Ranked neighbours

Models within 3 places of #135 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 32B: common questions

How does Qwen3 32B rank among AI models?

Qwen3 32B holds ModelCap Index position #135 of 248 ranked language models as of 22 September 2026, with an Index score of 37.6 (interval 31.6–43.6); evidence: measured. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.

How much does Qwen3 32B cost per 1M tokens?

Qwen3 32B is listed at $0.08 per 1M input tokens and $0.28 per 1M output tokens as of 22 September 2026 across 2 providers. 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 $0.30 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 32B?

Qwen3 32B has a published context window of 131K tokens (131,072) and a maximum output of 16K tokens. Individual providers can serve less than the published maximum; the providers table lists each endpoint's own limit.

Is Qwen3 32B 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/Qwen3-32B on Hugging Face.

Which API providers serve Qwen3 32B?

2 providers serve Qwen3 32B through OpenRouter as of 22 September 2026: DeepInfra and SiliconFlow. Each provider's price, context limit, quantization and measured uptime are in the providers table above.

Which benchmarks has Qwen3 32B been evaluated on?

Qwen3 32B has published results on 2 public boards tracked by ModelCap as of 22 September 2026: Arena coding 1407 (#193 of 397) and BFCL V4 48.7 (#24 of 83). Each board page ranks every tracked model on that benchmark; the ModelCap Index combines them with published uncertainty.

How does Qwen3 32B compare with Command A?

Qwen3 32B ranks #135 (Index 37.6) and Command A ranks #134 (Index 38.2) on the ModelCap Index as of 22 September 2026. The head-to-head page lines up their benchmarks, listed prices, context windows and provider counts side by side.

When was Qwen3 32B released?

Qwen3 32B first appeared in the catalogue on 28 Apr 2025, with a published knowledge cutoff of 2025-03-31. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.