Patchwire

Qwen · Released Feb 4, 2026

Qwen3 Coder Next

Qwen3-Coder-Next is an open-weight causal language model optimized for coding agents and local development workflows. It uses a sparse MoE design with 80B total parameters and only 3B activated per...

Open weights
Compare in showdown → OpenRouter ↗ All Qwen models
Released
Feb 4 2026
Context window
262K 236K out
Input / 1M tokens
$0.12
Output / 1M tokens
$0.80

Where to run it

Providers

Only Parasail serves Qwen3 Coder Next on OpenRouter right now.

ProviderInputOutputCache readContextMax outputUptimevs. best
ParasailBF16 $0.12 $0.80 $0.07262K236K98%24h Cheapest

Value

Price vs. performance

9 models score higher for the same price or lesson SciCode, e.g. GLM 5.3.
27.8%40.8%53.9%66.9% $0.01$0.10$1.00$10.00 DeepSeek V4.1 Flash 1017 (DeepSeek) — 51.8% · $0.30/1M in Gemini 4 Argon (Google) — 61.8% · $2.00/1M in Step 5 Preview (StepFun) — 58.9% · $1.00/1M in Claude Haiku 5.5 (Anthropic) — 55.0% · $0.10/1M in Mistral Large 4 (Mistral) — 54.2% · $0.68/1M in GPT-6.1 Sol (OpenAI) — 55.8% · $2.00/1M in Claude Sonnet 5.5 (Anthropic) — 61.0% · $2.00/1M in GPT-6 Luna (OpenAI) — 54.6% · $0.10/1M in GPT-6 Sol (OpenAI) — 57.6% · $2.00/1M in Claude Opus 5.5 (Anthropic) — 66.9% · $4.00/1M in MiMo-V2.6-Flash (Xiaomi) — 51.3% · $0.14/1M in MiMo-V2.6-Pro (Xiaomi) — 60.9% · $0.43/1M in Grok 4.7 (xAI) — 57.8% · $2.00/1M in DeepSeek V4.1 Flash (DeepSeek) — 51.8% · $0.056/1M in GPT-6 Astra (OpenAI) — 56.5% · $10.00/1M in Muse Spark 1.3 (Meta) — 59.7% · $1.25/1M in Gemini 3.8 Flash (Google) — 56.6% · $0.82/1M in Claude Fable 5.1 (Anthropic) — 63.1% · $10.00/1M in GLM 5.3 Flash (Z.ai) — 51.6% · $0.047/1M in GLM 5.3 (Z.ai) — 59.0% · $0.079/1M in Gemini 3.7 Flash (Google) — 59.8% · $0.75/1M in DeepSeek V4 Pro 0813 (DeepSeek) — 51.0% · $0.66/1M in Grok 4.6 (xAI) — 56.5% · $2.00/1M in Muse Spark 1.2 (Meta) — 57.4% · $1.25/1M in DeepSeek V4 Flash 0731 (DeepSeek) — 49.9% · $0.44/1M in Claude Opus 5 (Anthropic) — 56.4% · $5.00/1M in Gemini 3.6 Flash (Google) — 53.4% · $0.75/1M in Gemini 3.5 Flash Lite (Google) — 41.3% · $0.30/1M in Kimi K3 (Moonshot AI) — 59.5% · $0.24/1M in Muse Spark 1.1 (Meta) — 58.8% · $1.25/1M in GPT-5.6 Luna (OpenAI) — 53.6% · $0.20/1M in GPT-5.6 Terra (OpenAI) — 55.0% · $2.00/1M in GPT-5.6 Sol (OpenAI) — 57.8% · $4.00/1M in Grok 4.5 (xAI) — 55.0% · $2.00/1M in Claude Sonnet 5 (Anthropic) — 54.3% · $2.00/1M in GLM 5.2 (Z.ai) — 51.2% · $0.62/1M in Kimi K2.7 Code (Moonshot AI) — 47.8% · $0.67/1M in Claude Fable 5 (Anthropic) — 61.0% · $10.00/1M in MiniMax M3 (MiniMax) — 47.1% · $0.30/1M in Step 3.7 Flash (StepFun) — 40.1% · $0.20/1M in Claude Opus 4.8 (Anthropic) — 53.5% · $5.00/1M in Grok Build 0.1 (xAI) — 50.2% · $1.00/1M in Gemini 3.5 Flash (Google) — 53.9% · $1.50/1M in Gemini 3.1 Flash Lite (Google) — 43.4% · $0.25/1M in Grok 4.3 (xAI) — 48.3% · $1.25/1M in GPT-5.5 (OpenAI) — 56.1% · $5.00/1M in DeepSeek V4 Pro 0423 (DeepSeek) — 51.0% · $0.95/1M in DeepSeek V4 Flash 0423 (DeepSeek) — 49.9% · $0.091/1M in MiMo-V2.5-Pro (Xiaomi) — 50.2% · $0.43/1M in MiMo-V2.5 (Xiaomi) — 43.1% · $0.14/1M in Kimi K2.6 (Moonshot AI) — 53.5% · $0.65/1M in Claude Opus 4.7 (Anthropic) — 54.5% · $5.00/1M in GLM 5.1 (Z.ai) — 44.8% · $0.97/1M in Gemma 4 31B (Google) — 45.5% · $0.20/1M in MiniMax M2.7 (MiniMax) — 50.1% · $0.30/1M in GPT-5.4 Nano (OpenAI) — 47.2% · $0.20/1M in GPT-5.4 Mini (OpenAI) — 52.1% · $0.75/1M in Mistral Small 4 (Mistral) — 27.8% · $0.15/1M in GPT-5.4 (OpenAI) — 56.6% · $2.50/1M in Gemini 3.1 Flash Lite Preview (Google) — 43.4% · $0.25/1M in Gemini 3.1 Pro Preview (Google) — 58.7% · $2.00/1M in Claude Sonnet 4.6 (Anthropic) — 46.8% · $3.00/1M in Kimi K2.5 (Moonshot AI) — 49.0% · $0.50/1M in GLM 4.7 (Z.ai) — 45.1% · $0.54/1M in Mistral Large 3 2512 (Mistral) — 36.6% · $0.50/1M in DeepSeek V3.2 (DeepSeek) — 38.9% · $0.28/1M in GPT-5.1 (OpenAI) — 43.3% · $1.25/1M in Claude Haiku 4.5 (Anthropic) — 42.3% · $1.00/1M in GLM 4.6 (Z.ai) — 38.4% · $0.55/1M in Claude Sonnet 4.5 (Anthropic) — 45.7% · $3.00/1M in DeepSeek V3.2 Exp (DeepSeek) — 38.9% · $0.27/1M in DeepSeek V3.1 Terminus (DeepSeek) — 38.0% · $0.27/1M in GPT-5 (OpenAI) — 42.9% · $1.25/1M in GPT-5 Mini (OpenAI) — 39.2% · $0.25/1M in gpt-oss-120b (OpenAI) — 36.0% · $0.15/1M in gpt-oss-20b (OpenAI) — 38.9% · $0.018/1M in Gemini 2.5 Pro (Google) — 46.3% · $1.25/1M in Gemini 2.5 Pro Preview 06-05 (Google) — 46.3% · $1.25/1M in R1 0528 (DeepSeek) — 38.3% · $0.50/1M in Qwen3.8 Max (0902) (Qwen) — 53.2% · $2.00/1M in Qwen3.8 27B (Qwen) — 46.6% · $0.04/1M in Qwen3.7 Plus (Qwen) — 46.1% · $0.32/1M in Qwen3.7 Max (Qwen) — 49.5% · $1.48/1M in Qwen3.6 35B A3B (Qwen) — 36.6% · $0.10/1M in Qwen3.6 27B (Qwen) — 37.3% · $0.25/1M in Qwen3.6 Plus (Qwen) — 40.7% · $0.33/1M in Qwen3.5-9B (Qwen) — 29.5% · $0.10/1M in Qwen3.5-35B-A3B (Qwen) — 29.3% · $0.15/1M in Qwen3.5-122B-A10B (Qwen) — 35.6% · $0.26/1M in Qwen3 235B A22B Thinking 2507 (Qwen) — 41.4% · $0.45/1M in Qwen3 14B (Qwen) — 31.6% · $0.12/1M in Qwen3 32B (Qwen) — 35.4% · $0.08/1M in Qwen3 Coder Next (Qwen) — 36.2% · $0.12/1M in Qwen3 Coder Next

Qwen3 Coder Next Other Qwen Other labs Value frontier · SciCode vs. input price per 1M tokens (log scale) · Drag to pan, pinch or Ctrl + scroll to zoom, double-click to zoom in.

Benchmarks

2 benchmark scores

BenchmarkScoreRankLeader
SciCodeSoftware engineering · Research-coding problems from the natural sciences 36.2% #86of 93 Claude Opus 5.566.9%
CritPtReasoning & knowledge · Open-ended, research-level physics problems 0.0% #89of 96 GPT-5.6 Sol32.3%

Specs

Details

Model ID
qwen/qwen3-coder-next
Developer
Qwen
Release date
Feb 4, 2026 ·
Context window
262,144 tokens
Max output
235,929 tokens
API price
$0.12 / $0.80 per 1M input / output tokens
Providers
1
Input types
text
Reasoning
No
Tool calling
Yes
Open weights
Yes
Free tier
No

Release date, prices and providers from OpenRouter's catalog; buying directly from a provider can cost a little differently. Uptime is the share of OpenRouter requests each provider served over the last day. Benchmark scores are the best result per benchmark from Epoch AI, licensed CC BY 4.0. Rank counts every model tracked here with a score.