Qwen: Qwen3.5-9B

Public pricingIntelligence 81/100Large memoryVisionRéflexion approfondieOutils

Qwen: Qwen3.5-9B est un modèle multimodal conçu pour codage, débogage et travail technique. Il associe la gestion multimodale des entrées et de bonnes performances en codage, un contexte de 262K tokens et un profil à faible coût pour un travail fiable sur coding, debugging, and technical writing.

Input

$0.10/1M

Output

$0.15/1M

Cached

$0.01/1M

Batch

$0.03/1M

Calculate your Qwen3.5-9B bill.

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What would Qwen3.5-9B cost you?

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1,00010,00050,000250,0001M10M

Technical specifications

Qwen3.5-9B at a glance.

Memory

262,144

tokens

Max reply

32,768

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.

  • gpqa_diamond

    81.7

  • ifeval

    91.5

  • livecodebench

    65.6

  • mmlu_pro

    82.5

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 Qwen3.5-9B

  • 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

Qwen3.5-9B — 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, Qwen3.5-9B costs roughly $14 per month. Input is $0.10 /1M tokens and output is $0.15 /1M tokens.
Qwen3.5-9B 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, Qwen3.5-9B 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.
Qwen3.5-9B was released in February 2026, with training data cut off around October 2025.
Models in a similar class include Qwen3.5-Flash, Qwen3.5-35B-A3B, Qwen3.5-27B. The "Similar models" section below this FAQ links into each.

Still unsure?

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