Qwen: Qwen3.5-122B-A10B

Public pricingIntelligence 83/100Large memoryVisieDiep redenerenToolgebruik

Qwen: Qwen3.5-122B-A10B is een multimodaal-model voor beeld-taalbegrip. Het combineert multimodale invoerverwerking en beeldbegrip, een context van 262K tokens en een evenwichtig geprijsd-profiel voor betrouwbaar werk in image and video understanding. Het is een praktische keuze wanneer latentie, kosten en doorvoer belangrijk is, vooral voor teams die stabiele output,

Input

$0.26/1M

Output

$2.08/1M

Cached

$0.07/1M

Batch

$0.13/1M

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Technical specifications

Qwen3.5-122B-A10B 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.

  • gpqa_diamond

    86.6

  • ifeval

    93.4

  • livecodebench

    78.9

  • mmlu_pro

    86.7

  • swe_bench_verified

    72

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 Qwen3.5-122B-A10B

  • 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

Qwen3.5-122B-A10B — 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, Qwen3.5-122B-A10B costs roughly $103 per month. Input is $0.26 /1M tokens and output is $2.08 /1M tokens.
Qwen3.5-122B-A10B 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, Qwen3.5-122B-A10B 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.
Qwen3.5-122B-A10B was released in February 2026, with training data cut off around October 2025.
Models in a similar class include Qwen Plus 0728 (thinking), Qwen-Plus, Qwen3.5 Plus 2026-02-15. The "Similar models" section below this FAQ links into each.

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