- Instruction Following
Mistral Small 4 is an open-source multimodal Mixture-of-Experts model from Mistral that unifies text, image, reasoning, and coding capabilities in a single efficient system. It targets…
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DeepSeek V3.1 Nex N1
- Instruction Following
DeepSeek V3.1 Nex N1 is Nex AGI’s flagship post-trained variant of the DeepSeek V3.1 family, optimized for agent autonomy, tool use, and real‑world productivity. It offers strong reasoning, coding, and instruction-following performance with a 131K token context window at competitive prices.
Providers Comparison
Speed
Output tokens per second · Higher is better
L
LLM API
S
SiliconFlow (FP8)
G
GMI
C
CoreWeave
N
Novita
D
DeepSeek
P
Parasail (FP8)
D
DeepInfra (FP4)
End-to-End Response Time
Seconds · Lower is better
L
LLM API
S
SiliconFlow (FP8)
G
GMI
C
CoreWeave
N
Novita
D
DeepSeek
P
Parasail (FP8)
D
DeepInfra (FP4)
Price
USD per 1M tokens (blended) · Lower is better
L
LLM API
S
SiliconFlow (FP8)
G
GMI
C
CoreWeave
N
Novita
D
DeepSeek
P
Parasail (FP8)
D
DeepInfra (FP4)
About the model
What is DeepSeek V3.1 Nex N1?
DeepSeek V3.1 Nex N1 is a post-trained large language model from Nex AGI based on the DeepSeek V3.1 base that is optimized for agentic behavior, tool use, and practical applications. It is mainly used for building autonomous AI agents that can call tools and APIs reliably for real-world workflows. It is also widely applied to practical coding, HTML generation, and long-document business tasks thanks to its 131,072-token context window and solid instruction-following capabilities. The model is part of the Nex-N1 series of agent-focused DeepSeek V3.1 derivatives released by Nex AGI.
Model capabilities
5 Core Capabilities
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General Chat
Conducts multi-turn, instruction-following conversations, maintains context over long chats, and adapts tone for assistance, explanation, and ideation.
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Tool Calling
Calls external tools and functions from prompts, enabling agent workflows, automation, and integration with APIs for real-world productivity tasks.
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Code Generation
Generates and edits code and HTML, explains snippets, and assists with practical software development and debugging across varied scenarios.
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Reading Documents
Processes long text inputs using its large context window, summarizing, extracting information, and working across extensive documents or conversations.
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Multilingual Text
Understands and generates text in multiple languages, supporting cross-language communication and basic translation-style rewriting of content.
Use cases
6 Most Valuable Use Cases
- Autonomous AI Agents
- Tool-Based Workflows
- Practical Code Generation
- HTML Page Authoring
- Long-Context Document Help
- Business Process Automation
Transparent pricing
Cost Comparison
LLM API offers the lowest cost and fastest access to DeepSeek V3.1 Nex N1–class models.
| Provider | Region | Latency | Throughput | Uptime | Input ($/1M) | Output ($/1M) | Context |
|---|---|---|---|---|---|---|---|
| LLM API BEST | Global | ~180ms | ~120 tps | ~99.99% | ~$0.09 | ~$0.27 | ~256K tokens |
| Nex AGI | Global | ~240ms | ~80 tps | ~99.9% | ~$0.11 | ~$0.33 | ~256K tokens |
| OpenRouter | Global | ~260ms | ~70 tps | ~99.9% | ~$0.12 | ~$0.36 | ~200K tokens |
| Together AI | US East | ~220ms | ~75 tps | ~99.9% | ~$0.13 | ~$0.39 | ~128K tokens |
| Fireworks AI | US West | ~230ms | ~65 tps | ~99.9% | ~$0.14 | ~$0.42 | ~128K tokens |
Performance benchmarks
Technical Specifications
| Metric | DeepSeek V3.1 Nex N1 | OpenAI o3-mini | Anthropic Claude 3.5 Sonnet |
|---|---|---|---|
| Avg Latency | ~180ms | ~220ms | ~250ms |
| Context Window | 128K | 200K | 200K |
| Input Price ($/1M) | $0.50 | $0.15 | $3.00 |
| Output Price ($/1M) | $1.50 | $0.60 | $15.00 |
| Max Output Tokens | 8K | 4K | 4K |
| Throughput | ~120 tps | ~90 tps | ~70 tps |
| Uptime | 99.9% | 99.9% | 99.9% |
30-day usage via LLM API
- 620M
- API requests (last 30 days)
- 95B
- Prompt tokens processed
- 138B
- Completion tokens generated
- 99.96%
- Avg uptime
Architecture & Integration
Why Build on LLM.API?
One unified API. Every major model. Built-in reliability, cost control, and observability.
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Unified AI Routing
Automatically route each request to the optimal model across providers based on latency, cost, or quality—without changing your integration or redeploying code.
One endpoint, every model -
Cost-Aware Orchestration
Define spend policies once and let LLM.API dynamically pick cheaper equivalents, downgrade for non-critical paths, and prevent runaway bills with centralized limits and controls.
Control spend by design -
Resilient Fallbacks
Stay online when a provider degrades or fails. LLM.API automatically retries and fails over to backup models, preserving SLAs without extra error-handling logic.
Built-in high availability -
Deep Observability
Get per-request traces, logs, costs, and latencies across all providers in one place, making debugging, optimization, and regression detection straightforward.
See every token -
Task-Level Abstractions
Define tasks like chat, RAG, tools, or classification once and let LLM.API pick the right model and prompt template for each environment.
Code to tasks, not models -
High-Throughput Batch
Submit large batches of prompts through a single API and let LLM.API handle concurrency, rate limits, retries, and aggregation for massive offline workloads.
Scale jobs, not plumbing
Decision guide
When to Use — When NOT to Use
Use it if...
- You need a general-purpose LLM from Nex AGI for everyday coding and writing.
- You need a reasonably capable model for chatbots that handle mixed technical and casual queries.
- Your use case involves prototyping AI assistants where top-tier state-of-the-art is unnecessary.
- You need a single model to cover translation, summarization, and light data extraction.
- Your use case involves integrating with an existing Nex AGI toolchain or infrastructure.
- You need decent reasoning on moderate-length prompts without extremely long context windows.
Avoid if...
- You need rigorously benchmarked, frontier-level performance comparable to the very latest flagship models.
- Your workload requires guaranteed support for extremely long context, like hundreds of thousands tokens.
- You need strong, independently audited safety, compliance, and enterprise governance certifications.
- Your workload requires extensive ecosystem tooling, plugins, and community examples around the model.
- You need formally published, transparent benchmarks across coding, reasoning, and multilingual tasks.
- Your workload requires proven, large-scale production adoption with mature SLAs and uptime guarantees.
FAQ
Frequently Asked Questions
-
What is DeepSeek V3.1 Nex N1?
DeepSeek V3.1 Nex N1 is a large language model from Nex AGI optimized for fast, general-purpose text generation and reasoning via LLM.API.
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What is DeepSeek V3.1 Nex N1 best suited for?
DeepSeek V3.1 Nex N1 is best for code generation, data-aware assistants, and complex reasoning over medium-length contexts in production applications.
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How is DeepSeek V3.1 Nex N1 priced on LLM.API?
DeepSeek V3.1 Nex N1 uses a pay-per-token billing model on LLM.API, with separate input and output token rates defined in your workspace pricing.
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What is the context window of DeepSeek V3.1 Nex N1?
DeepSeek V3.1 Nex N1 supports a context window of up to 32,000 tokens for combined prompt and completion.
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How fast is DeepSeek V3.1 Nex N1 on LLM.API?
DeepSeek V3.1 Nex N1 typically returns first tokens within a second, with overall latency depending on prompt size and completion length.
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What modalities does DeepSeek V3.1 Nex N1 support?
DeepSeek V3.1 Nex N1 currently supports text input and text output only through LLM.API.
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How do I call DeepSeek V3.1 Nex N1 through LLM.API?
Set the model field to "DeepSeek V3.1 Nex N1" in your LLM.API completion or chat endpoint request using your existing API key.
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How does DeepSeek V3.1 Nex N1 compare to similar models?
DeepSeek V3.1 Nex N1 targets a balance of strong reasoning and lower cost, comparable to mid-to-high tier general-purpose LLMs.
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Does DeepSeek V3.1 Nex N1 support tools or function calling?
You can orchestrate tools around DeepSeek V3.1 Nex N1 using LLM.API routing or your own function-calling layer in application code.
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What are the main limitations of DeepSeek V3.1 Nex N1?
DeepSeek V3.1 Nex N1 can hallucinate, lacks real-time knowledge, and may struggle with extremely long, multi-step workflows beyond its context window.
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