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DeepSeek V3.2 Exp

deepseek/v3-2-exp

Par DeepSeek · famille: deepseek · sorti 2025-09-29 · fin de connaissance: 2025-01-01

$0.220
Entrée / 1M jetons
$0.330
Sortie / 1M jetons
164K
Fenêtre de contexte
164K
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 · 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.

Coding63
  • Tool calling40/40
  • Structured output0/20
  • Reasoning10/10
  • Context window (100K → 1M)4/20
  • Provider availability9/10
Agents74
  • Tool calling35/35
  • Structured output0/25
  • Reasoning15/15
  • Output token limit15/15
  • Provider availability9/10
JSON / structured output49
  • Structured output / JSON mode0/50
  • Tool calling20/20
  • Temperature control10/10
  • Price-friendly for high-volume19/20
Cost efficiency69
  • Headline price (log-scaled)69/95
  • Has prompt-cache pricing0/5
Long context51
  • Context window (100K → 2M)41/90
  • Has published price for full window10/10
Production-readiness96
  • Number of independent providers40/40
  • Has published per-token price20/20
  • Context window ≥ 8K15/15
  • No data inconsistencies across providers6/10
  • 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
$1.27
< $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
$2.53
< $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
$0.60
< $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
$2.09
< $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
$2.84
< $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 zenmux · deepseek/deepseek-v3.2-exp

$0.220
Entrée
$0.330
Sortie

Disponible chez 9 fournisseurs

FournisseurID modèle fournisseurEntrée / 1MSortie / 1MContextePublié le
Vercel AI Gateway
vercel
deepseek/deepseek-v3.2-exp$0.270$0.400164K2025-09-29
NanoGPT
nano-gpt
deepseek-ai/deepseek-v3.2-exp$0.280$0.420164K2025-09-29
Alibaba (China)
alibaba-cn
deepseek-v3-2-exp$0.287$0.431131K2025-01-01
ZenMux
zenmux
deepseek/deepseek-v3.2-exp$0.220$0.330163K2025-09-29
NovitaAI
novita-ai
deepseek/deepseek-v3.2-exp$0.270$0.410164K2025-09-29
Qiniu
qiniu-ai
deepseek/deepseek-v3.2-expUnknownUnknown128K2025-09-29
Kilo Gateway
kilo
deepseek/deepseek-v3.2-exp$0.270$0.410164K2025-01-01
Meganova
meganova
deepseek-ai/DeepSeek-V3.2-Exp$0.270$0.400164K2025-10-10
SiliconFlow
siliconflow
deepseek-ai/DeepSeek-V3.2-Exp$0.270$0.410164K2025-10-10

Incohérences de données entre fournisseurs

  • context_window varies: 128000, 131072, 163000, 163840, 164000
  • release_date varies (span 282d): 2025-01-01, 2025-09-29, 2025-10-10

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 DeepSeek V3.2 Exp cost?

DeepSeek V3.2 Exp costs $0.220 per 1M input tokens and $0.330 per 1M output tokens, sourced from zenmux. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.

What is the context window of DeepSeek V3.2 Exp?

DeepSeek V3.2 Exp has a context window of 164K tokens, with a max output of 164K tokens per reply. This is the total combined size of prompt + completion.

Does DeepSeek V3.2 Exp support tool calling?

Yes. DeepSeek V3.2 Exp 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 DeepSeek V3.2 Exp support structured output / JSON mode?

Support for structured output / JSON-schema-constrained decoding is not reported for DeepSeek V3.2 Exp in our data source. Verify with DeepSeek's official documentation before relying on it in production.

Can DeepSeek V3.2 Exp accept image input?

No. DeepSeek V3.2 Exp only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.

Is DeepSeek V3.2 Exp open-weight?

No. DeepSeek V3.2 Exp is a proprietary model — only DeepSeek (and any approved hosting partners) can serve it. The pricing above reflects the cheapest API access.

What are the best alternatives to DeepSeek V3.2 Exp?

If DeepSeek V3.2 Exp doesn't fit, consider DeepSeek-V3.2, DeepSeek V4 Pro, DeepSeek-R1-0528. 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 DeepSeek 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.