Qwen3.5-27B

Language Alibaba Qwen Verified Released Feb 23, 2026
  • In Input modalities: TextImageVideo Out Output modalities: Text
  • Reasoning
  • Reasoning can be off
  • Tool use
  • Structured output
  • Open weights

Prices

6 offerings · prices as listed
Alibaba Cloud Model Studio (opens in a new tab) Official Global · USD qwen3.5-27b
Conditions/ 1M tokensInputOutput
Standard $0.086$0.688
Prompts over 128K tokens $0.258$2.064

Prices from Alibaba Cloud Model Studio pricing (opens in a new tab) (checked Nov 2, 2026)

Alibaba Cloud Model Studio (opens in a new tab) Official International · USD qwen3.5-27b
Conditions/ 1M tokensInputOutput
Standard $0.30$2.40

Prices from Alibaba Cloud Model Studio pricing (opens in a new tab) (checked Nov 2, 2026)

Alibaba Cloud Model Studio (opens in a new tab) Official China · CNY qwen3.5-27b
Conditions/ 1M tokensInputOutput
Standard ¥0.60¥4.80
Prompts over 128K tokens ¥1.80¥14.40

Prices from 阿里云百炼:模型价格 (opens in a new tab) (checked Nov 2, 2026)

Alibaba Cloud Model Studio (opens in a new tab) Official Germany (global scope) · US (global scope) · USD qwen3.5-27b
Conditions/ 1M tokensInputOutput
Standard no longer listed since Oct 21, 2026 $0.086$0.688
Prompts over 128K tokens no longer listed since Oct 21, 2026 $0.258$2.064

Prices from Alibaba Cloud Model Studio pricing (opens in a new tab) (checked Nov 2, 2026)

Standard: the price a request with no conditions pays (the headline price elsewhere on the site).

Details

Max thinking budget
81.92K
Licence
apache-2.0
Family
qwen
Model ID

Not stated on Alibaba Qwen’s pages: max input, reasoning efforts, built-in tools, knowledge cutoff, aliases.

Run locally

Weights: Qwen/Qwen3.5-27B
  • Parameters 27.8B
  • Dense
  • Native precision BF16
  • Layers 64
  • KV cache per token 64 KB
  • Native context 256K (model card)
  • Config positions 256K (config.json max_position_embeddings)
  • API context 256K (maker’s API)
My hardware GeForce RTX 4090 24 GB · 1008 GB/s · 64 GB DDR5 dual channel · 89.6 GB/s
On your hardware · GeForce RTX 4090
Runs well Q5_0 (automatic) 8K context 26–38 tok/sOne GPU
WeightsKV cacheOverheadUsable
Needs
≈ 19.2 GB (weights 17.8 + KV cache 0.5 + overhead 0.9)
Usable
21.6 GB (90% of its memory)
Generation speed
26–38 tok/s
Longest context
46K (longer doesn’t fit)
First token
about 0.90–1.35 s for a 2K prompt
PrecisionWeightsNeeds at 8KOn your hardwareLongest context
BF16 (native)maker’s file51.7 GB≈ 54.8Doesn’t fit—
Q8_027.5 GB≈ 29.4Needs system memory 4–6 tok/s—
FP8maker’s file28.7 GB≈ 30.7Needs system memory 4–6 tok/s—
Q6_K21.2 GB≈ 22.8Needs system memory 13–20 tok/s—
Q5_K_M18.4 GB≈ 19.8Runs well 25–37 tok/s36K
Q5_017.8 GB≈ 19.2Runs well 26–38 tok/s46K
Q4_K_M15.7 GB≈ 17.0Runs well 29–43 tok/s81K
Q4_014.6 GB≈ 15.8Runs well 31–47 tok/s101K
INT4 (AWQ / GPTQ)maker’s file28.2 GB≈ 30.1Needs system memory 4–6 tok/s—
IQ4_XS13.7 GB≈ 14.9Runs well 33–49 tok/s115K
Q3_K_Mquality drops12.6 GB≈ 13.8Runs well 36–54 tok/s133K
IQ3_XXSquality drops9.9 GB≈ 10.9Runs well 45–68 tok/s179K
Q2_Kquality drops9.7 GB≈ 10.7Runs well 46–69 tok/s182K
IQ2_XXSquality drops6.7 GB≈ 7.7Runs well 66–98 tok/s231K

Click a row to choose a precision. “Maker’s file” sizes are the maker’s own files; others are parameters × bits per weight.

Compared with other hardware

Each at the highest precision it runs. Click one for details.

Smallest that runs it (Q4_K_M, 8K): GPU GeForce RTX 4090; unified memory Apple M6 (24GB or 32GB) · 32 GB.

Run commands

The maker publishes no files at this precision. Choose its native precision or one of its own builds, or quantise it yourself with llama.cpp.

Memory to fine-tune
Full≈ 418.0 GBDoesn’t fit your hardware
LoRA≈ 56.3 GBDoesn’t fit your hardware
QLoRA≈ 19.1 GBFits your hardware

Batch 1, 2,048-token sequences, gradient checkpointing; LoRA and QLoRA train rank-16 adapters on the attention projections.

Estimates; facts from the maker’s Hugging Face repositories, as of 2026-11-06. How it’s estimated

Cited scores

From third-party leaderboards, not measured by us
  • LMArena Text 1,409

    #95 of 163 listed models · CI 1,405–1,413 · 28,647 votes

  • EQ-Bench Longform Writing 59

    #61 of 92 listed models

  • LMArena Text · Chinese 1,472

    #72 of 161 listed models · CI 1,459–1,485 · 2,063 votes

  • LMArena Text · Coding 1,451

    #95 of 163 listed models · CI 1,444–1,459 · 7,929 votes

  • LMArena (Arena), leaderboard-dataset on Hugging Face, licensed CC BY 4.0 · License · as of Oct 19 – 28, 2026
  • EQ-Bench by Samuel J. Paech (eqbench.com; EQ-bench/EQ-bench-site on GitHub), MIT License. · License · as of Oct 28, 2026
  • changes we made
  1. Context window 256K → 262.14K
  2. 3 new prices on SiliconFlow, China Input ¥0.60 · Output ¥4.80 · Output (Prompts over 128K tokens) ¥14.40
  3. 2 prices dropped on Alibaba Cloud Model Studio, International Output (Reasoning off) $2.40 · Output (Reasoning on) $2.40

Sources

Alibaba Qwen’s official policies: data use, privacy, terms →

Alibaba Qwen · China · qwen.ai

Snapshots, the same family and other models from this provider