Qwen 3 235B A22B Instruct 2507

Web searchFunction calling
Advertised as qwen-3-235b-a22b-instruct-2507qwen3-235bqwen3-235b-a22bqwen3-235b-a22b-instruct-2507qwen3-235b-instruct
Quick reference
Qwen 3 235B A22B Instruct 2507 — TLDR
  • 🧠 Mixture-of-experts: 235B total parameters, 22B active per token
  • 🆕 Updated "non-thinking" refresh of the original Qwen3-235B-A22B
  • 📏 Natively supports 256K context, extendable toward 1M tokens
  • 🎯 Gains in instruction following, math, science, coding, tool use
  • 🌐 Multilingual coverage across many languages and dialects
  • 🔧 Function calling and web search; Qwen-Agent tooling support
  • 🔒 Apache 2.0 licensed open weights
  • 💬 Instruct-only mode; does not emit reasoning traces
💰 Best price on AntSeed
FREE / FREE100%
per 1M · cheapest in / out
📏 Context
128K tokens
🐜 Sellers
9
advertising on AntSeed
Provider

Alibaba Group is a Chinese multinational technology company founded in 1999 and headquartered in Hangzhou, Zhejiang. Originally built around e-commerce and cloud computing, Alibaba has become one of the most prolific contributors to open-weight AI research, developing the Qwen…

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About this model

Qwen 3 235B A22B Instruct 2507 is a Mixture-of-Experts large language model from Alibaba's Qwen team, with 235 billion total parameters but only about 22 billion activated per forward pass. It is the "2507" refresh of the original Qwen3-235B-A22B non-thinking mode, released as part of the Qwen3 series. Distributed under the Apache 2.0 license, it targets long-document research, technical work, and high-precision tasks, and is served here in FP8 quantization.

Compared with its same-family predecessor, the original Qwen3-235B-A22B, Qwen reports significant improvements in general capabilities — instruction following, logical reasoning, text comprehension, mathematics, science, coding and tool usage — plus substantial gains in multilingual long-tail knowledge and better alignment on subjective, open-ended tasks. The update also adds enhanced 256K-token long-context understanding, with model-card instructions for extending toward one million tokens. Unlike the original dual-mode design, this Instruct variant operates in non-thinking mode only and does not generate reasoning-trace blocks.

For workloads needing explicit step-by-step reasoning, Qwen released a parallel Qwen 3 235B A22B Thinking 2507 sibling that uses extended reasoning chains. Other related Qwen text models in the catalog include the efficiency-focused Qwen 3 Next 80B. Note that Venice exposes a 128K context window for this deployment, below the model's full native 256K capacity.

View source on GitHub ↗View model card on HuggingFace ↗
Sources
huggingface.coQwen/Qwen3-235B-A22B-Instruct-2507 · Hugging Face· huggingface.co

This About section is AI-generated from public sources via VeniceStats + Venice inference, with no human editing. It may contain inaccuracies.

Usage on AntSeed
Tokens served
3.55M
input + output
Requests
474
settled calls
Buyers
8
distinct, on this model
Sellers used
7
of 9 advertising
Settled
$0.28
gross USDC, this model
Sellers serving Qwen 3 235B A22B Instruct 2507 (9)compare on the network explorer →
SellerReputationRoutingInput $/MCached $/MOutput $/MCategoriesAPI

"Best price" and the seller table are live AntSeed catalog data (advertised $/1M tokens — or $ per generated image for unit-billed image models — not settled amounts). Reputation = on-chain trust (0-100). "Routing" = the SDK's default buyer routing (what the VPR desktop app ships with): a trust ≥ 60 gate on the effective reputation, then cheapest-first among routable sellers; live failover state (per-peer cooldowns) is buyer-side runtime and not included. Model knowledge (TLDR, provider, About) via the VeniceStats enrichment layer. Advertised catalog, not the model used in any specific purchase. "Usage on AntSeed" counts only settlements whose buyers share the per-model split on-chain (metadata v2/v3, opt-in), so every usage figure is a lower bound.