Qwen 3.6 35B-A3B

Overview

Alibaba's agentic coding MoE with 35B total and just 3B active parameters, released April 16, 2026. Scores 73.4% on SWE-Bench while running on a single 24GB GPU.

When to pick this model

• Local SWE-Bench-grade coding agents
• Single 24GB GPU coding workstations
• Repository-scale refactoring with 262K context
• Cost-sensitive autonomous coding pipelines
• Commercial code assistants under Apache 2.0

VRAM requirements by quantization

Quantization	VRAM required
Q4_K_M (recommended)	21 GB
Q5_K_M	25 GB
Q8_0	38 GB
FP16 (no quantization)	70 GB

VRAM figures include model weights plus a typical 8k KV cache and ~600 MB runtime overhead (Ollama / llama.cpp baseline). Add headroom for higher context lengths.

Published benchmark scores

Benchmark	Score
SWE-Bench	73.4

Scores published by the model author or aggregated from public leaderboards. Re-measured monthly by our editorial team.

Strengths

• 73.4% SWE-Bench in an MoE that fits on a 24GB GPU
• Only 3B active parameters means fast inference
• 262K context handles whole repos
• Apache 2.0 license

Limitations

• No official Ollama tag yet
• Brand-new release with limited production track record
• Specialized for coding, weaker as a general chat model

Architecture & training

Architecture: MoE 35B/3B active · agentic-coding specialist

Training: Released April 16, 2026.

Quick start

ollama run qwen3.6:35b-a3b

Or use the open-source MCP server to query this model from Claude Desktop, Cursor, or any MCP-compatible client.