Qwen: Qwen3.5-27B

Public pricingIntelligence 82/100Large memoryVisionRéflexion approfondieOutils

Qwen: Qwen3.5-27B est un modèle multimodal conçu pour compréhension vision-langage. Il associe la gestion multimodale des entrées et la compréhension d’images, un contexte de 262K tokens et un profil à faible coût pour un travail fiable sur image and video understanding.

Input

$0.20/1M

Output

$1.56/1M

Cached

$0.03/1M

Batch

$0.05/1M

Calculate your Qwen3.5-27B bill.

Set your workload — see cost at your exact volume.

What would Qwen3.5-27B cost you?

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Technical specifications

Qwen3.5-27B at a glance.

Memory

262,144

tokens

Max reply

65,536

tokens

Memory tier

Large

an entire book or large codebase

Tokenizer

qwen3

Released

Feb 2026

Training cutoff

Oct 2025

Availability

Public pricing

Status

active

Benchmarks

Quality benchmarks

Independent evaluations from public leaderboards. Higher is better.

  • mmlu_pro

    86.1

  • gpqa_diamond

    85.5

  • ifeval

    95

  • livecodebench

    80.7

What it can do

Capabilities & limits.

  • Understands images
  • Deep step-by-step thinking
  • Uses tools / calls functions
  • Strict JSON output
  • Streams replies
  • Fine-tunable on your data

When to pick Qwen3.5-27B

  • Multi-step reasoning, research agents, or hard math.
  • Screenshot analysis, image understanding, or document OCR.
  • Agentic workflows that call tools or APIs.
  • Long documents, full codebases, or extensive chat histories.

When to look elsewhere

  • Very latency-sensitive, real-time apps where every millisecond counts.

Alternatives

Similar models to compare.

FAQ

Qwen3.5-27B — the questions we see most.

Pricing, capabilities, alternatives — generated from the same data that powers the calculator above.

Get instant answers from our AI agent

At a typical workload of 50,000 conversations a month with 1,500-token prompts and 800-token replies, Qwen3.5-27B costs roughly $77 per month. Input is $0.20 /1M tokens and output is $1.56 /1M tokens.
Qwen3.5-27B has a 262,144-token context window (large memory — an entire book or large codebase). That means you can fit about 49,152 words of input and history in a single call.
Beyond text generation, Qwen3.5-27B supports understanding images, deep step-by-step reasoning, calling functions / tools, strict JSON output, fine-tuning on your own data. It streams replies by default.
Qwen3.5-27B was released in February 2026, with training data cut off around October 2025.
Models in a similar class include Qwen3.5-35B-A3B, Qwen Plus 0728 (thinking), Qwen-Plus. The "Similar models" section below this FAQ links into each.

Still unsure?

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