
DeepSeek · Chat / LLM · 685B Parameters · 128K Context

Streaming Reasoning Code Long Context Agentic Tool Use ChatOverview
DeepSeek V3.2 is DeepSeek’s frontier open-source model with 685B total parameters and novel DeepSeek Sparse Attention (DSA) that reduces long-context computational cost by 50%. Trained with a scalable RL framework across 1,800+ agentic environments, it achieves performance comparable to GPT-5 — earning gold-medal results at both the 2025 IMO and IOI. With integrated reasoning and tool-use capabilities through large-scale agentic synthesis, DeepSeek V3.2 represents a landmark in open-source frontier AI. Served instantly via the Qubrid AI Serverless API.🏆 Gold-medal IMO 2025 & IOI 2025. GPT-5-class performance. Fully open-source. Deploy via Qubrid AI — no H100 cluster required.
Model Specifications
| Field | Details |
|---|---|
| Model ID | deepseek-ai/DeepSeek-V3.2 |
| Provider | DeepSeek |
| Kind | Chat / LLM |
| Architecture | DeepSeek Sparse Attention (DSA) MoE Transformer — 685B total, 256 experts per layer (8 activated per token), MLA attention |
| Parameters | 685B total |
| Context Length | 128,000 Tokens |
| MoE | No |
| Release Date | December 2025 |
| License | MIT |
| Training Data | Large-scale diverse corpus + RL post-training with 1,800+ agentic environments and 85,000 complex prompts |
| Function Calling | Not Supported |
| Image Support | N/A |
| Serverless API | Available |
| Fine-tuning | Coming Soon |
| On-demand | Coming Soon |
| State | 🟢 Ready |
Pricing
💳 Access via the Qubrid AI Serverless API with pay-per-token pricing. No infrastructure management required.
| Token Type | Price per 1M Tokens |
|---|---|
| Input Tokens | $0.56 |
| Input Tokens (Cached) | $0.28 |
| Output Tokens | $1.68 |
Quickstart
Prerequisites
- Create a free account at platform.qubrid.com
- Generate your API key from the API Keys section
- Replace
QUBRID_API_KEYin the code below with your actual key
💡 Temperature note: Use 1.0 (default) for optimal performance with this model.
Python
JavaScript
Go
cURL
Live Example
Prompt: Explain quantum computing in simple terms
Response:
Playground Features
The Qubrid AI Playground lets you interact with DeepSeek V3.2 directly in your browser — no setup, no code, no cost to explore.🧠 System Prompt
Define the model’s role, reasoning depth, and output constraints before the conversation begins — essential for agentic workflows, structured analysis, and complex multi-turn tasks.Set your system prompt once in the Qubrid Playground and it applies across every turn of the conversation.
🎯 Few-Shot Examples
Guide the model’s reasoning approach and output format with concrete examples — no fine-tuning, no retraining required.| User Input | Assistant Response |
|---|---|
Prove that there are infinitely many prime numbers | Assume finitely many primes p₁...pₙ. Let N = (p₁×p₂×...×pₙ) + 1. N is either prime (contradiction) or divisible by a prime not in our list (contradiction). Therefore infinitely many primes exist. ∎ |
Write a binary search in Python | def binary_search(arr, target): l, r = 0, len(arr)-1 \n while l <= r: \n mid = (l+r)//2 \n if arr[mid] == target: return mid \n elif arr[mid] < target: l = mid+1 \n else: r = mid-1 \n return -1 |
💡 Stack multiple few-shot examples in the Qubrid Playground to dial in reasoning depth, output format, and domain focus — no fine-tuning required.
Inference Parameters
| Parameter | Type | Default | Description |
|---|---|---|---|
| Streaming | boolean | true | Enable streaming responses for real-time output |
| Temperature | number | 1 | Recommended 1.0 for optimal performance |
| Max Tokens | number | 8192 | Maximum number of tokens to generate |
| Top P | number | 0.95 | Controls nucleus sampling |
Use Cases
- Advanced reasoning and agent tasks
- Long-horizon agentic tool use
- Mathematical competition problems (IMO/IOI level)
- Code generation and complex debugging
- Enterprise automation
- Long-context document analysis
Strengths & Limitations
| Strengths | Limitations |
|---|---|
| DeepSeek Sparse Attention — 50% compute savings on long contexts | 128K max context window |
| GPT-5-class performance on reasoning benchmarks | Requires H100/H200 class infrastructure for full self-hosting |
| Gold-medal IMO 2025 and IOI 2025 performance | No official Jinja chat template — custom encoding required |
| 685B MoE with efficient inference (8 experts activated per token) | Tool calling may need warm-up on cold-start phases |
| Integrated reasoning into tool-use via RL synthesis | Function calling not supported via API |
| MIT License — fully open source |
Why Qubrid AI?
- 🚀 No infrastructure setup — 685B MoE served serverlessly, pay only for what you use
- 🔁 OpenAI-compatible — drop-in replacement using the same SDK, just swap the base URL
- 💰 Cached input pricing — $0.28/1M for cached tokens, dramatically reducing costs on repeated long contexts
- 🧪 Built-in Playground — prototype with system prompts and few-shot examples instantly at platform.qubrid.com
- 📊 Full observability — API logs and usage tracking built into the Qubrid dashboard
- 🌐 Multi-language support — Python, JavaScript, Go, cURL out of the box
Resources
| Resource | Link |
|---|---|
| 📖 Qubrid Docs | docs.platform.qubrid.com |
| 🎮 Playground | Try DeepSeek V3.2 live |
| 🔑 API Keys | Get your API Key |
| 🤗 Hugging Face | deepseek-ai/DeepSeek-V3.2 |
| 💬 Discord | Join the Qubrid Community |
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Frontier models. Serverless infrastructure. Zero friction.