DeepSeek V3.2 Exp
deepseek/v3-2-expVon DeepSeek · Familie: deepseek · veröffentlicht 2025-09-29 · Wissensstand: 2025-01-01
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
Fähigkeiten
Model fit scores
0–100 · higher is betterThese 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.
Coding83
- Tool calling40/40
- Structured output20/20
- Reasoning10/10
- Context window (100K → 1M)4/20
- Provider availability9/10
Agents99
- Tool calling35/35
- Structured output25/25
- Reasoning15/15
- Output token limit15/15
- Provider availability9/10
JSON / structured output99
- Structured output / JSON mode50/50
- 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.
| Scenario | Cost | Assumption |
|---|---|---|
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. |
Preis-Details
Empfohlene Preise von zenmux · deepseek/deepseek-v3.2-exp
Bei 9 Anbietern verfügbar
| Anbieter | Anbieter-Modell-ID | Eingabe / 1M | Ausgabe / 1M | Kontext | Veröffentlicht |
|---|---|---|---|---|---|
| OpenRouter openrouter | deepseek/deepseek-v3.2-exp | $0.270 | $0.410 | 164K | 2025-09-29 |
| Qiniu qiniu-ai | deepseek/deepseek-v3.2-exp | Unknown | Unknown | 128K | 2025-09-29 |
| Alibaba (China) alibaba-cn | deepseek-v3-2-exp | $0.287 | $0.431 | 131K | 2025-01-01 |
| NovitaAI novita-ai | deepseek/deepseek-v3.2-exp | $0.270 | $0.410 | 164K | 2025-09-29 |
| ZenMux zenmux | deepseek/deepseek-v3.2-exp | $0.220 | $0.330 | 163K | 2025-09-29 |
| SiliconFlow siliconflow | deepseek-ai/DeepSeek-V3.2-Exp | $0.270 | $0.410 | 164K | 2025-10-10 |
| Kilo Gateway kilo | deepseek/deepseek-v3.2-exp | $0.270 | $0.410 | 164K | 2025-01-01 |
| Meganova meganova | deepseek-ai/DeepSeek-V3.2-Exp | $0.270 | $0.400 | 164K | 2025-10-10 |
| NanoGPT nano-gpt | deepseek-ai/deepseek-v3.2-exp | $0.280 | $0.420 | 164K | 2025-09-29 |
Datenunterschiede zwischen Anbietern
- context_window varies: 128000, 131072, 163000, 163840, 164000
- release_date varies (span 282d): 2025-01-01, 2025-09-29, 2025-10-10
Anbieter melden unterschiedliche Werte für dieses Modell. Die Schnellinfos oben nutzen den repräsentativen Anbieter; pro Anbieter siehe Tabelle.
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 66K 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?
Yes. DeepSeek V3.2 Exp 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 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?
Yes. DeepSeek V3.2 Exp'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 DeepSeek V3.2 Exp?
If DeepSeek V3.2 Exp doesn't fit, consider DeepSeek V4 Pro, DeepSeek-V3.2, DeepSeek V4 Flash. 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 are normalised into a single canonical model record and reconciled with each provider's official documentation. We re-pull daily and write any changes (price, context, capability) to the /changelog page.
Explore more
More DeepSeek models
- DeepSeek V4 Pro$0.43 in / $0.87 out
- DeepSeek-V3.2$0.18 in / $0.35 out
- DeepSeek V4 Flash$0.14 in / $0.28 out
- DeepSeek-R1$0.40 in / $1.70 out
- DeepSeek-R1-0528$0.40 in / $1.70 out
Capability lists this model is in
Zuletzt aktualisiert:
Pricing and capabilities are refreshed daily and reconciled against each provider's official documentation. Always verify critical production decisions with the provider directly.