Qwen3.5 122B A10B
Intelligence benchmarks
Artificial Analysis indexes - compared with the best open and proprietary models
Intelligence
17.7
AA Index
Coding
43.3
AA Index
Intelligence Index - Qwen3.5 122B A10B vs. the field
Best open-weight models (you can run locally) and leading proprietary models for context.
Coding Index comparison
Benchmark data from Artificial Analysis · updated 2026-10-19.
Hosted API cost & speed
What it costs to rent this model instead of running it locally
| Metric | Value |
|---|---|
| Input (per 1M tokens) | $0.40 |
| Output (per 1M tokens) | $3.20 |
| Median speed (hosted API) | 143 tok/s |
Median across hosted providers, measured by Artificial Analysis - updated 2026-10-19. Local llama.cpp speed depends on your hardware — see the hardware pages for estimates.
Arena rating (LMArena)
Human preference wins from head-to-head chat battles
| Metric | Value |
|---|---|
| Overall arena rating | 1417.4 |
| Rank (overall) | #123 |
| Battle votes | 29,732 |
Overall rating published by LMArena on 2026-10-15 - a pairwise human-preference Elo across live chat battles; higher is better. Fetched 2026-10-19. Open-weights models compete head-to-head with proprietary ones here — no benchmark prompts, just what people pick.
Standard benchmarks
Performance across standard evaluations
| Benchmark | Score |
|---|---|
| GPQA Diamond | 82.7 |
| HLE | 15.9 |
| IFBench | 50.8 |
| Terminal-Bench | 29.5 |
Source: Artificial Analysis component evals - updated 2026-10-19.
Will it run on your hardware?
Pick your GPU memory - see which quantizations fit, and the cheapest card for the rest
Need an exact figure for your context length? Use the VRAM calculator.
Run it locally
Copy-paste - running in under a minute
vllm serve Qwen/Qwen3.5-122B-A10B-FP8New to this? Start with Ollama · serve to many users with vLLM.
Deep dive
Notes, sources, and the full write-up
Qwen3.5 122B A10B is a 125.1B-parameter apache-2.0 model from Alibaba. It scores 17.7 on the Artificial Analysis Intelligence Index (coding 34.7). At Q4_K_M it needs roughly 73 GB of VRAM, placing it in the 48 GB+ / multi-GPU hardware tier.
Benchmarks
Artificial Analysis Intelligence Index - Qwen3.5 122B A10B vs. leading closed models:
| Model | Intelligence | Coding | GPQA |
|---|---|---|---|
| Qwen3.5 122B A10B | 41.6 | 34.7 | 85.7 |
| GPT-5.5 (xhigh) | 60.2 | 59.1 | 93.5 |
| Claude Opus 4.8 (max) | 61.4 | 56.7 | 92 |
| Gemini 3.1 Pro Preview | 57.2 | 55.5 | 94.1 |
| Grok 4.3 (high) | 53.2 | 41 | 90.1 |
Source: Artificial Analysis (2026-06-07).
Popularity
Qwen3.5 122B A10B has 1,337,559 downloads in the last month on HuggingFace and 101 likes.
Frequently asked
Quick answers to common questions
How much VRAM does Qwen3.5 122B A10B need?
Qwen3.5 122B A10B with 125.1B parameters needs approximately 73 GB at Q4_K_M quantization. Use our VRAM calculator for an exact estimate.
Is Qwen3.5 122B A10B better than other Qwen models?
Qwen3.5 122B A10B has 125.1B parameters with 262,144 context - a strong choice for general use.
What license is Qwen3.5 122B A10B under?
Qwen3.5 122B A10B is released under the apache-2.0 license, making it suitable for most commercial and personal projects.
What hardware runs Qwen3.5 122B A10B well?
With 125.1B parameters, Qwen3.5 122B A10B requires adequate VRAM. High-end GPUs like the RTX 4090 (24GB), RTX 5090 (32GB), or Mac Studio with unified memory are good options. Check our hardware directory for specific recommendations.
What is the best quantization for Qwen3.5 122B A10B?
Q4_K_M is the recommended sweet spot - ~98% of FP16 quality at ~27% of the size. Q5_K_M (~89 GB) is an option if you have spare VRAM. Use our VRAM calculator to compare.
How long can Qwen3.5 122B A10B's context window handle?
Qwen3.5 122B A10B supports a 262,144-token context window - enough for very long documents, codebases, or multi-turn conversations. Real-world usable context may vary by implementation.
What models compete with Qwen3.5 122B A10B?
Qwen3.5 122B A10B competes with other 63B–188B. Browse our model directory for comparisons, benchmarks, and community reviews to find the best fit.
Nearby options
Similar models and compatible hardware by spec