Intelligence des modèles d'IA

Qwen3 Coder

alibaba/qwen3-coder

Par Alibaba (Qwen) · famille: qwen · sorti 2025-07-23 · fin de connaissance: 2025-04

$0.220
Entrée / 1M jetons
$0.950
Sortie / 1M jetons
262K
Fenêtre de contexte
67K
Sortie max

Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.

Capacités

Tool callingRaisonnementSortie structuréePièces jointesPoids ouvertsContrôle de température
Modalités: entrée text · sortie text

Model fit scores

0–100 · higher is better

These scores reward declared capabilities, context size, price and provider availability — they are not benchmark results. Use them as a directional signal alongside your own evaluation.

Coding75
  • Tool calling40/40
  • Structured output20/20
  • Reasoning0/10
  • Context window (100K → 1M)8/20
  • Provider availability7/10
Agents82
  • Tool calling35/35
  • Structured output25/25
  • Reasoning0/15
  • Output token limit15/15
  • Provider availability7/10
JSON / structured output98
  • Structured output / JSON mode50/50
  • Tool calling20/20
  • Temperature control10/10
  • Price-friendly for high-volume18/20
Cost efficiency61
  • Headline price (log-scaled)61/95
  • Has prompt-cache pricing0/5
Long context61
  • Context window (100K → 2M)51/90
  • Has published price for full window10/10
Production-readiness89
  • Number of independent providers35/40
  • Has published per-token price20/20
  • Context window ≥ 8K15/15
  • No data inconsistencies across providers4/10
  • Official model (not derivative)15/15

Cost Efficiency Index

Open full calculator →

Estimated cost using the recommended provider's headline rate. Each scenario fixes average input/output tokens — the assumptions are shown in the third column.

ScenarioCostAssumption
RAG answer
per 1,000 RAG answers
$1.57
< $0.01 per request
5K input tokens (query + 4 retrieved chunks of ~1K each) and a 500-token answer. Typical SaaS knowledge-base bot.
Support ticket triage
per 10,000 tickets
$3.15
< $0.01 per request
1K input tokens (ticket body + system prompt) and a 100-token JSON classification reply. High-volume customer support.
Data extraction
per 1,000 documents
$0.92
< $0.01 per request
2K input tokens (a single document page) and a 500-token JSON extraction. ETL / invoice / form pipelines.
Code review
per 1,000 PRs
$2.71
< $0.01 per request
8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads.
Agent step
per 1,000 steps
$3.21
< $0.01 per request
12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step.

Détail des tarifs

Tarif recommandé de helicone · qwen3-coder

$0.220
Entrée
$0.950
Sortie

Disponible chez 7 fournisseurs

FournisseurID modèle fournisseurEntrée / 1MSortie / 1MContextePublié le
OpenRouter
openrouter
qwen/qwen3-coder$0.300$1.20262K2025-07-23
Vercel AI Gateway
vercel
alibaba/qwen3-coder$0.380$1.53262K2025-04
NanoGPT
nano-gpt
TEE/qwen3-coder$1.50$2.00128K2025-07-23
Kilo Gateway
kilo
qwen/qwen3-coder$0.220$1.00262K2025-07-23
OpenCode Zen
opencode
qwen3-coder$0.450$1.80262K2025-07-23
Helicone
helicone
qwen3-coder$0.220$0.950262K2025-07-23
FastRouter
fastrouter
qwen/qwen3-coder$0.300$1.20262K2025-07-23

Incohérences de données entre fournisseurs

  • context_window varies: 128000, 262144
  • release_date varies (span 113d): 2025-04, 2025-07-23
  • modalities varies across offerings

Les fournisseurs rapportent des valeurs différentes pour ce modèle. Les infos clés ci-dessus utilisent un fournisseur représentatif ; voir le tableau pour le détail par fournisseur.

Frequently asked questions

How much does Qwen3 Coder cost?

Qwen3 Coder costs $0.220 per 1M input tokens and $0.950 per 1M output tokens, sourced from helicone. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.

What is the context window of Qwen3 Coder?

Qwen3 Coder has a context window of 262K tokens, with a max output of 67K tokens per reply. This is the total combined size of prompt + completion.

Does Qwen3 Coder support tool calling?

Yes. Qwen3 Coder supports tool calling (function calling). This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.

Does Qwen3 Coder support structured output / JSON mode?

Yes. Qwen3 Coder supports structured output / JSON-schema-constrained decoding. This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.

Can Qwen3 Coder accept image input?

No. Qwen3 Coder only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.

Is Qwen3 Coder open-weight?

Yes. Qwen3 Coder's weights are publicly available, so you can self-host or fine-tune. Note that open weights ≠ open source — the training data and code are typically not released.

What are the best alternatives to Qwen3 Coder?

If Qwen3 Coder doesn't fit, consider Qwen3.5 397B-A17B, Qwen3 32B, Qwen3 235B A22B Instruct 2507. Each one targets the same use case — see the Related links below for direct head-to-head pages.

Where does this data come from?

All numbers come from the public models.dev API and are normalised into a single canonical model record. We re-pull daily and write any changes (price, context, capability) to the /changelog page.

Dernière mise à jour :

Data is sourced from models.dev and normalized for comparison. Prices and capabilities may change. Always verify critical production decisions with the provider's official documentation.