Qwen (Alibaba)
A Tier · 8.8/10
Alibaba's open-weights + API family -- Qwen 3.7 Max flagship GA (May 20 2026: SWE-Bench Pro 60.6%, Terminal-Bench 69.7%, GPQA 92.4%, $2.50/$7.50 per 1M with 50% promo until 6/22), Qwen3.7-Plus multimodal API (Jun 2), Qwen3.6-27B dense Apache 2.0 (beats the 397B MoE on coding from one consumer GPU)
Score Breakdown
Benchmark Scores
Benchmarks for Qwen3.5-397B MoE
| Benchmark | Description | Score | |
|---|---|---|---|
| MMLU-Pro | Harder multi-subject reasoning | 83.5% | |
| GPQA Diamond | Graduate-level science questions | 78.2% | |
| AIME 2025 | 87% | ||
| HumanEval | Python code generation | 92.5% | |
| SWE-Bench Verified | 69.4% |
Last updated: 2026-04-13
Personality & Tone
The multilingual Alibaba all-rounder
Tone: Helpful, verbose, and notably strong in Chinese and other non-English languages. Qwen is chattier than Mistral or DeepSeek and tends toward structured, multi-section replies.
Quirks: Best-in-class at Chinese -- occasionally switches to Mandarin mid-response for technical or cultural topics even when prompted in English. Political refusal patterns mirror other Chinese models on China-specific topics.
The Good and the Bad
What we like
- +Qwen 3.6-Plus (launched Mar 30 2026) is Alibaba's answer to Claude Opus 4.5 on agentic coding -- native 1M context, always-on CoT reasoning, and tool-use baked into the base model. Matches Claude on SWE-bench per Alibaba Cloud's published benchmarks
- +Qwen3.5 Small (0.8B / 2B / 4B / 9B) is the most capable sub-10B open-weight family in 2026 -- the 2B runs on iPhone in airplane mode, the 9B matches 120B-class models on reasoning benchmarks. Apache 2.0 on all of it
- +Qwen3.5-Omni (Mar 30 2026) is the first native multimodal open-weight model with realtime text/audio/video inputs and outputs in one unified model -- displaces needing 3 separate models for voice + vision + text
- +Full modality lineup Apache 2.0: text (Qwen3, 3.5), vision (Qwen3-VL), coder (Qwen3-Coder-Next), reasoning (Qwen3-Thinking), omni-multimodal (Qwen3.5-Omni)
- +Qwen3-Coder-Next 80B-A3B runs on 8 GB VRAM and still posts top-tier coding benchmarks (sparse MoE activates only ~3B params)
- +Massive ecosystem: Ollama, llama.cpp, vLLM, LM Studio, Hugging Face all ship first-class Qwen quants within days of release
What could be better
- −Qwen3-Max flagship is API-only -- you can't self-host the best Alibaba model
- −Censorship on politically sensitive topics (PRC regulations apply)
- −English writing style occasionally stilted compared to Claude or Mistral
- −Rapid release cadence means model names (Qwen3, Qwen3.5, Qwen3-Next, Qwen3-Max-Thinking) are confusing
Pricing
Self-hosted (Free)
- ✓Apache 2.0 license on open weights
- ✓Available on Hugging Face, ModelScope, Ollama
- ✓Fine-tuning fully permitted
API (OpenRouter / Alibaba Cloud)
- ✓Qwen3-Coder-Next 80B-A3B: $0.12 in / $0.60 out
- ✓Qwen3.5-397B: $0.40 in / $2.40 out
- ✓Qwen3-Max (API only): $0.78 in / $6.00 out
API (Qwen 3.6-Plus flagship, Mar 30 2026)
- ✓Native 1M context window
- ✓Always-on chain-of-thought reasoning
- ✓Agentic tool-use baked in (matches Claude Opus 4.5 on SWE-bench per Alibaba Cloud)
- ✓API-only (weights not released)
API (Qwen 3.7 Max flagship, May 20 2026 -- CLOSED WEIGHTS)
- ✓Vendor benchmarks: SWE-Bench Pro 60.6%, Terminal-Bench 2.0-Terminus 69.7%, GPQA 92.4%
- ✓PROPRIETARY / API-only on DashScope + Model Studio
- ✓Qwen3.7-Plus sibling (Jun 2): multimodal image/video input at $0.40/$1.60 per 1M
API (Qwen 3.6-Max-Preview, Apr 20 2026 -- CLOSED WEIGHTS)
- ✓#1 on SWE-bench Pro, Terminal-Bench 2.0, SciCode, QwenClawBench, QwenWebBench
- ✓256K context window (text-only at launch, no vision)
- ✓OpenAI- and Anthropic-API-compatible endpoints
- ✓Alibaba's FIRST flagship shipped without open weights -- proprietary only
- ✓Available via Qwen Studio + Alibaba Cloud Model Studio
Self-hosted (Qwen3.6-27B dense, Apr 22 2026)
- ✓Apache 2.0 open weights -- no commercial restrictions
- ✓DENSE 27B (not MoE) -- all params active, simpler to deploy than sparse-MoE flagships
- ✓Multimodal: text + image + video, 262K native context (extensible to ~1M)
- ✓Runs on a single consumer-tier GPU (RTX 4090 or equivalent at FP16; smaller VRAM at quant)
- ✓BEATS Qwen3.5-397B-A17B MoE flagship on coding while being ~15x smaller in active params
System Requirements
Hardware needed to self-host. Min = smallest viable setup (usually heavy quantization). Max = full-precision / production-grade.
| Model variant | Min | Max |
|---|---|---|
| Qwen3-Coder-Next 80B-A3B (sparse MoE) | 8 GB VRAM Q4 (RTX 3060) | 1× A100 80 GB FP16 |
| Qwen3.5 (397B MoE flagship) | 128 GB RAM + 24 GB GPU (Q3) | 4× H100 FP8 |
| Qwen3-VL (vision flagship) | 24 GB VRAM (Q4) | 1× H100 FP16 |
| Qwen3-Max | API-only -- weights not released | API-only -- weights not released |
| Qwen3.6-35B-A3B (sparse MoE, vision-language, Apr 16 2026)Apache 2.0 open weights. SWE-bench 73.4% -- current best for open-weights coding. | 8 GB VRAM Q4 (RTX 3060 tier; ~3B active params keep inference cheap) | 1x A100 80 GB FP16 or 2x RTX 4090 for 262K+ context |
Known Issues
- USER-CREATED AI AGENTS SHUT DOWN 2026-07-15 (announced ~7/4-7/6, tier-1 press): Alibaba's Qwen app (and ByteDance's Doubao, simultaneously) is **discontinuing its AI agent-creation features on July 15, 2026 -- and ALL existing user-created agents stop functioning**, including humanlike 'AI companion' agents. Driver: China's 'Interim Measures for the Administration of Anthropomorphic AI Interaction Services' takes effect the same day. Users keep temporary access to agent configurations and chat histories during a transition window and are advised to back up before **October 15**, when related data becomes unrecoverable. This is a consumer-app change -- the Qwen models/API are unaffected. Separately (SCMP, early July, press-reported): Alibaba cut Qwen3.7-Max by ~80% and Qwen3.7-Plus by ~60% for international users on the Qoder platform during off-peak hours (10pm-8am Beijing = US working hours) -- an explicit play for US developer demand amid a broader Chinese token price warSource: Bloomberg (2026-07-06), TechNode (technode.com/2026/07/06/bytedances-doubao-and-alibabas-qwen-to-shut-down-ai-agent-features-on-july-15/), SCMP · 2026-07-15
- FLAGSHIP GA + VENDOR NUMBERS CONFIRMED (verified 2026-06-09): **Qwen 3.7 Max** shipped 2026-05-20 ('Qwen3.7: The Agent Frontier' on the official Qwen blog) -- the benchmark figures that circulated in aggregators are now vendor-published: **SWE-Bench Pro 60.6%, Terminal-Bench 2.0-Terminus 69.7%, GPQA 92.4%**, plus SWE-Multilingual 78.3%, SciCode 53.5%, QwenSVG 1608. PROPRIETARY / API-only on DashScope/Model Studio. Official pricing: **$2.50/M input, $7.50/M output list -- with a 50% launch promo ($1.25/$3.75) running until 2026-06-22**. Separately, **Qwen3.7-Plus** launched ~2026-06-02 on Bailian/Model Studio: multimodal (image + video input, text output) with GUI-agent, deep reasoning, and tool invocation at $0.40/$1.60 per 1M -- press-reported agent scores (ScreenSpot Pro 79.0, AndroidWorld 81.0) await vendor tables. Both models confirmed on Alibaba's official Model Studio model listSource: Qwen blog (qwen.ai/blog?id=qwen3.7), Alibaba Cloud pricing campaign (alibabacloud.com/campaign/qwen-discount), Alibaba Model Studio model list (help.aliyun.com/zh/model-studio/models), VentureBeat (Qwen3.7-Plus) · 2026-06-09
- INTERPRETABILITY RELEASE (2026-05-01): Alibaba released **Qwen-Scope** -- an open-source suite of **sparse autoencoder (SAE) weights** for the Qwen3 and Qwen3.5 model families, plus inference + visualization tooling. SAEs decompose internal model activations into interpretable feature directions (Anthropic / Google DeepMind have been the highest-profile labs publishing this style of interpretability work; Alibaba is the first major Chinese lab to ship SAE weights openly). Practical implication: researchers and red-teamers can now probe Qwen3.5 internals (feature attribution, concept steering, refusal-circuit analysis) without training their own SAEs -- a multi-month / multi-GPU effort. Adds to Qwen's open-weights story even as the Qwen 3.6 flagship line goes closed-weights. Materially raises the floor for safety / alignment research on Chinese open-weight families.Source: Qwen blog (qwen.ai/blog?id=qwen-scope) · 2026-05-01
- Qwen3.6-27B dropped 2026-04-22 (~48h after Max-Preview) as the new open-weights coding champion. DENSE 27B, NOT MoE -- all params active, simpler to deploy. Apache 2.0 open weights with no commercial restrictions. Multimodal: text + image + video. 262K native context (extensible to ~1M). Verified benchmarks: SWE-bench Verified 77.2%, SWE-bench Pro 53.5%, Terminal-Bench 2.0 59.3% (matches Claude Opus 4.5 exactly), MMLU-Pro 86.2%, GPQA Diamond 87.8%, AIME 2026 94.1%, MMMU-Pro 75.8%. Notably BEATS the Qwen3.5-397B-A17B MoE flagship on coding from a single consumer GPU -- this displaces the 35B-A3B as the open-weights centerpiece for most users. Quants from unsloth + mlx-community shipped same weekSource: qwen.ai/blog?id=qwen3.6-27b, HuggingFace Qwen/Qwen3.6-27B, implicator.ai analysis · 2026-04-22
- Qwen 3.6-Max-Preview launched 2026-04-20 as Alibaba's first flagship shipped WITHOUT open weights -- #1 across SWE-bench Pro, Terminal-Bench 2.0, SciCode, QwenClawBench, and QwenWebBench. 256K context, text-only (no vision at launch), APIs compatible with OpenAI + Anthropic SDKs for easy swap-in. Signals Alibaba's pivot toward closed flagships while keeping mid-size models open. If you picked Qwen for the 'best open weights' story, the best model is no longer open -- but the 3.6-27B Apache 2.0 dense released 48 hours later mostly closes that complaint for non-frontier coding workloadsSource: Decrypt, CNTechPost · 2026-04
- CRITICAL (2026-04-15): Qwen Code free OAuth tier discontinued. Alibaba throttled from 1,000 -> 100 free requests/day before fully cutting it. To keep using Qwen Code you now need an Alibaba Cloud Coding Plan (~$50/mo), BYOK via OpenRouter / Fireworks / Cerebras, or local inference on your own hardware via Ollama/vLLM. The 'free open-source AI' framing no longer applies to hosted access -- only to self-hosted deploymentSource: Decrypt, GitHub QwenLM/qwen-code issues #3316 · 2026-04
- Qwen3.6-35B-A3B open-weights release on 2026-04-16 is the open-model story of April. Sparse MoE with 35B total / 3B active, vision-language multimodal, Apache 2.0, 262K native context (extensible to ~1M). Benchmarks are best-in-class for open weights: SWE-bench Verified 73.4% (vs Gemma 4-31B 52%), AIME 2026 92.7, GPQA Diamond 86.0, MMMU 81.7 (beats Claude Sonnet 4.5 at 79.6), Terminal-Bench 2.0 51.5%. Simon Willison's pelican-drawing test favored Qwen3.6-35B-A3B over Claude Opus 4.7 -- a high-signal community endorsementSource: Hugging Face Qwen3.6-35B-A3B, Alibaba Cloud announcement, Simon Willison, MarkTechPost, buildfastwithai review · 2026-04
- Qwen3-Max and now Qwen 3.6-Max-Preview are both API-only -- the pattern suggests Alibaba has quietly adopted closed-weights for flagships while keeping sub-flagship sizes Apache 2.0. Confusing for users expecting Alibaba's best model to be self-hostableSource: Reddit r/LocalLLaMA, Decrypt · 2026-04
- Refuses discussion of Tiananmen, Taiwan sovereignty, Xi Jinping -- same PRC content filters as DeepSeekSource: Hugging Face discussions · 2026-01
Best for
Developers who want frontier-tier open weights with Apache 2.0 licensing. Qwen3-Coder-Next is arguably the best local coding model; Qwen3.5-397B is a top-3 open generalist.
Not for
Teams that need the Qwen3-Max flagship self-hostable (it's API-only), or use cases that touch Chinese-government-sensitive topics.
Our Verdict
Qwen is the most complete open-weights family in 2026. Alibaba ships Apache-2.0 weights across text, coding, vision, and reasoning -- every modality has a top-tier entry. Qwen3-Coder-Next is a standout: 3B active params but competitive with Claude Sonnet on coding. The catch is that Qwen3-Max, the absolute flagship, stays closed. If you can live with the PRC content filters and want the best open-weights ecosystem, Qwen is the S-tier pick.
Sources
- Qwen blog: Qwen3.7 -- The Agent Frontier (vendor benchmarks) (accessed 2026-06-09)
- Alibaba Cloud: Qwen 3.7 Max pricing + launch discount (accessed 2026-06-09)
- Alibaba Model Studio model list (qwen3.7-max + qwen3.7-plus) (accessed 2026-06-09)
- Decrypt: Alibaba Qwen 3.7 Max preview review (2026-05) (accessed 2026-05-26)
- Qwen blog: Qwen3.6-27B dense Apache 2.0 (2026-04-22) (accessed 2026-04-27)
- HuggingFace Qwen/Qwen3.6-27B (accessed 2026-04-27)
- Implicator.ai: Qwen3.6-27B beats 397B MoE on coding (accessed 2026-04-27)
- Decrypt: Qwen 3.6-Max-Preview launch (accessed 2026-04-21)
- CNTechPost: Qwen3.6-Max-Preview release notes (accessed 2026-04-21)
- Decrypt: Qwen Code free tier shutdown (accessed 2026-04-21)
- Qwen blog: Qwen 3.6-Plus towards real-world agents (accessed 2026-04-17)
- Alibaba Cloud: Qwen 3.6-Plus for agentic AI (accessed 2026-04-17)
- Hugging Face Qwen collection (accessed 2026-04-17)
- OpenRouter pricing (accessed 2026-04-17)
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