aiticker

Qwen · Released Feb 25, 2026

Qwen3.5-122B-A10B

The Qwen3.5 122B-A10B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. In terms of...

ReasoningOpen weightsVision
Compare in showdown → OpenRouter ↗ All Qwen models
Released
Feb 25 2026
Context window
262K 66K out
Input / 1M tokens
$0.40 from $0.11
Output / 1M tokens
$3.20 from $0.90

Where to run it

23 providers compared

Cheapest: AIHubMix at $0.11 / $0.90 per 1M input / output tokens — 85% less than the priciest option.

ProviderInputOutputCache readContextMax outputUptimevs. best
AIHubMix $0.11 $0.90 —262K66K— Cheapest
Merge Gateway $0.12 $0.92 $0.023131K33K— +2%
OrcaRouter $0.12 $0.92 —262K66K— +2%
EmpirioLabs AI $0.12 $0.92 $0.12256K64K— +2%
SiliconFlow (China) $0.12 $0.96 —262K66K— +6%
Alibaba $0.26 $2.08 —262K66K100%24h +131%
SiliconFlowFP8 · no tool calling $0.26 $2.08 —262K236K96.7%24h +131%
NanoGPT $0.26 $2.08 $0.10262K33K— +131%
Kilo Gateway $0.26 $2.08 —262K66K— +131%
Neon $0.22 $2.20 —262K25K— +131%
Ofox $0.29 $2.29 $0.29256K64K— +155%
Deep Infra $0.29 $2.40 —262K66K— +164%
AtlasCloudFP8 $0.30 $2.40 $0.30262K66K99.6%24h +166%
NovitaBF16 $0.40 $3.20 —262K66K99.7%24h +255%
LLM Gateway $0.40 $3.20 —262K66K— +255%
Mixlayer $0.40 $3.20 —262K262K— +255%
Jalapeno Cloud $0.40 $3.20 —262K66K— +255%
Novita AI $0.40 $3.20 —262K66K— +255%
DevPass (LLM Gateway) $0.40 $3.20 —262K66K— +255%
Hugging Face $0.40 $3.20 —262K66K— +255%
TensorX $0.50 $3.50 $0.13262K262K— +303%
Infomaniak $0.50 $3.97 —200K66K— +341%
Regolo AI $1.12 $4.71 —262K16K— +551%

Value

Price vs. performance

34 models score higher for the same price or lesson SciCode, e.g. Kimi K3.
13.2%31.1%49.0%66.9% $0.001$0.01$0.10$1.00$10.00 DeepSeek V4.1 Flash 1017 (DeepSeek) — 51.8% · $0.15/1M 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% · $1.36/1M 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% · $0.30/1M 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% · $0.005/1M 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% · $0.034/1M 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% · $0.30/1M in MiMo-V2.5 (Xiaomi) — 43.1% · $0.12/1M 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% · $1.40/1M 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 GPT-4.1 Mini (OpenAI) — 40.4% · $0.40/1M in GPT-4.1 Nano (OpenAI) — 25.9% · $0.10/1M in Gemma 3 12B (Google) — 16.4% · $0.05/1M in Gemma 3 27B (Google) — 23.3% · $0.08/1M in o3 Mini (OpenAI) — 42.8% · $1.10/1M in Llama 3.3 70B Instruct (Meta) — 26.0% · $0.10/1M in Mistral Large 2407 (Mistral) — 36.6% · $2.00/1M in Llama 3.1 8B Instruct (Meta) — 13.2% · $0.05/1M in Mistral Large (Mistral) — 36.6% · $2.00/1M 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% · $0.08/1M in Qwen3.5-35B-A3B (Qwen) — 29.3% · $0.14/1M in Qwen3 Coder Next (Qwen) — 36.2% · $0.12/1M 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 Qwen3.5-122B-A10B (Qwen) — 35.6% · $0.40/1M in Qwen3.5-122B-A10B

Qwen3.5-122B-A10B 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

3 benchmark scores

BenchmarkScoreRankLeader
SciCodeSoftware engineering · Research-coding problems from the natural sciences 35.6% #92of 102 Claude Opus 5.566.9%
CritPtReasoning & knowledge · Open-ended, research-level physics problems 0.9% #83of 111 GPT-5.6 Sol32.3%
LMCAReasoning & knowledge · Judge the quality of conceptual arguments like experts 32.2% #75of 123 Claude Sonnet 5.568.3%

Specs

Details

Model ID
qwen/qwen3.5-122b-a10b
Developer
Qwen
Release date
Feb 25, 2026 ·
Context window
262,144 tokens
Max output
65,536 tokens
API price
$0.40 / $3.20 per 1M input / output tokens
Providers
23
Input types
text, image, video
Reasoning
Yes
Tool calling
Yes
Open weights
Yes
Free tier
No

Release date and prices from OpenRouter's catalog; providers from OpenRouter and models.dev. Buying directly from a provider can cost a little differently. Speed, latency and uptime are measured on OpenRouter only; 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.