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Qwen3.6 35B A3B Thinking

nano-gpt/qwen3-6-35b-a3b-thinking

Par nano-gpt · famille: qwen3.6 · sorti 2026-04-19

⚠ Il s'agit d'un fine-tune communautaire ou dérivé — pas d'une publication officielle de l'éditeur.

$0.290
Entrée / 1M jetons
$1.74
Sortie / 1M jetons
262K
Fenêtre de contexte
16K
Sortie max

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

Capacités

✗ Tool calling✓ Raisonnement✗ Sortie structurée✗ Pièces jointes✓ Poids ouverts? Contrôle de température
Modalités: entrée text, image, video · 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.

Coding19
  • Tool calling0/40
  • Structured output0/20
  • Reasoning10/10
  • Context window (100K → 1M)8/20
  • Provider availability1/10
Agents26
  • Tool calling0/35
  • Structured output0/25
  • Reasoning15/15
  • Output token limit10/15
  • Provider availability1/10
JSON / structured output16
  • Structured output / JSON mode0/50
  • Tool calling0/20
  • Temperature control0/10
  • Price-friendly for high-volume16/20
Cost efficiency55
  • Headline price (log-scaled)55/95
  • Has prompt-cache pricing0/5
Long context61
  • Context window (100K → 2M)51/90
  • Has published price for full window10/10
Vision82
  • Accepts image input50/50
  • Context window (10K → 1M)21/30
  • Has published price10/10
  • Provider availability1/10
Production-readiness50
  • Number of independent providers5/40
  • Has published per-token price20/20
  • Context window ≥ 8K15/15
  • No data inconsistencies across providers10/10
  • Official model (not derivative)0/15

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
$2.32
< $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
$4.64
< $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
$1.45
< $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
$4.06
< $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
$4.52
< $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 nano-gpt · qwen/Qwen3.6-35B-A3B:thinking

$0.290
Entrée
$1.74
Sortie

Disponible chez 1 fournisseurs

FournisseurID modèle fournisseurEntrée / 1MSortie / 1MContextePublié le
NanoGPT
nano-gpt
qwen/Qwen3.6-35B-A3B:thinking$0.290$1.74262K2026-04-19

Frequently asked questions

How much does Qwen3.6 35B A3B Thinking cost?

Qwen3.6 35B A3B Thinking costs $0.290 per 1M input tokens and $1.74 per 1M output tokens, sourced from nano-gpt. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.

What is the context window of Qwen3.6 35B A3B Thinking?

Qwen3.6 35B A3B Thinking has a context window of 262K tokens, with a max output of 16K tokens per reply. This is the total combined size of prompt + completion.

Does Qwen3.6 35B A3B Thinking support tool calling?

No. Qwen3.6 35B A3B Thinking does not support tool calling (function calling). If your workflow requires it, look at the /capabilities/tool-calling list for alternatives.

Does Qwen3.6 35B A3B Thinking support structured output / JSON mode?

No. Qwen3.6 35B A3B Thinking does not support structured output / JSON-schema-constrained decoding. If your workflow requires it, look at the /capabilities/structured-output list for alternatives.

Can Qwen3.6 35B A3B Thinking accept image input?

Yes. Qwen3.6 35B A3B Thinking accepts both text and image input. Vision pricing per image is usually billed on top of the regular token rate — check nano-gpt's docs for the exact rule.

Is Qwen3.6 35B A3B Thinking open-weight?

Yes. Qwen3.6 35B A3B Thinking'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 Qwen3.6 35B A3B Thinking?

If Qwen3.6 35B A3B Thinking doesn't fit, consider Brave (Answers), Exa (Research), Auto model (Basic). 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.

Explore more

More nano-gpt models

Capability lists this model is in

See also

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.