DeepSeek-V3.2-Speciale
deepseek/v3-2-specialePor DeepSeek · familia: deepseek · lanzado 2025-12-01 · fecha de conocimiento: 2024-07
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
Capacidades
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.
Coding17
- Tool calling0/40
- Structured output0/20
- Reasoning10/10
- Context window (100K → 1M)2/20
- Provider availability5/10
Agents35
- Tool calling0/35
- Structured output0/25
- Reasoning15/15
- Output token limit15/15
- Provider availability5/10
JSON / structured output29
- Structured output / JSON mode0/50
- Tool calling0/20
- Temperature control10/10
- Price-friendly for high-volume19/20
Cost efficiency67
- Headline price (log-scaled)67/95
- Has prompt-cache pricing0/5
Long context45
- Context window (100K → 2M)35/90
- Has published price for full window10/10
Production-readiness81
- Number of independent providers25/40
- 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 | $1.55 < $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 | $3.11 < $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 | $0.74 < $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 | $2.57 < $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 | $3.49 < $0.01 per request | 12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step. |
Detalle de precios
Precio recomendado de openrouter · deepseek/deepseek-v3.2-speciale
Disponible en 5 proveedores
| Proveedor | ID de modelo del proveedor | Entrada / 1M | Salida / 1M | Contexto | Lanzado |
|---|---|---|---|---|---|
| Azure azure | deepseek-v3.2-speciale | $0.580 | $1.68 | 128K | 2025-12-01 |
| OpenRouter openrouter | deepseek/deepseek-v3.2-speciale | $0.270 | $0.410 | 164K | 2025-12-01 |
| NanoGPT nano-gpt | deepseek/deepseek-v3.2-speciale | $0.280 | $0.420 | 163K | 2025-12-02 |
| Kilo Gateway kilo | deepseek/deepseek-v3.2-speciale | $0.400 | $1.20 | 164K | 2025-12-01 |
| Azure Cognitive Services azure-cognitive-services | deepseek-v3.2-speciale | $0.580 | $1.68 | 128K | 2025-12-01 |
Inconsistencias de datos entre proveedores
- context_window varies: 128000, 163000, 163840
- modalities varies across offerings
Los proveedores reportan valores distintos para este modelo. Los datos clave de arriba usan un proveedor representativo; consulta la tabla para detalles por proveedor.
Frequently asked questions
How much does DeepSeek-V3.2-Speciale cost?
DeepSeek-V3.2-Speciale costs $0.270 per 1M input tokens and $0.410 per 1M output tokens, sourced from openrouter. 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-Speciale?
DeepSeek-V3.2-Speciale has a context window of 128K tokens, with a max output of 128K tokens per reply. This is the total combined size of prompt + completion.
Does DeepSeek-V3.2-Speciale support tool calling?
No. DeepSeek-V3.2-Speciale does not support tool calling (function calling). If your workflow requires it, look at the /capabilities/tool-calling list for alternatives.
Does DeepSeek-V3.2-Speciale support structured output / JSON mode?
Support for structured output / JSON-schema-constrained decoding is not reported for DeepSeek-V3.2-Speciale in our data source. Verify with DeepSeek's official documentation before relying on it in production.
Can DeepSeek-V3.2-Speciale accept image input?
No. DeepSeek-V3.2-Speciale only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.
Is DeepSeek-V3.2-Speciale open-weight?
Yes. DeepSeek-V3.2-Speciale'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-Speciale?
If DeepSeek-V3.2-Speciale 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
- DeepSeek-V3.2$0.26 in / $0.38 out
- DeepSeek V4 Pro$1.74 in / $3.48 out
- DeepSeek-R1-0528$0.40 in / $1.70 out
- DeepSeek-R1$0.40 in / $1.70 out
- DeepSeek-V3.1$0.20 in / $0.70 out
Capability lists this model is in
Última actualización:
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.