Author's Description
DeepSeek-V3.1 Terminus is an update to [DeepSeek V3.1](/deepseek/deepseek-chat-v3.1) that maintains the model's original capabilities while addressing issues reported by users, including language consistency and agent capabilities, further optimizing the model's performance in coding and search agents. It is a large hybrid reasoning model (671B parameters, 37B active) that supports both thinking and non-thinking modes. It extends the DeepSeek-V3 base with a two-phase long-context training process, reaching up to 128K tokens, and uses FP8 microscaling for efficient inference. Users can control the reasoning behaviour with the `reasoning` `enabled` boolean. [Learn more in our docs](https://openrouter.ai/docs/use-cases/reasoning-tokens#enable-reasoning-with-default-config) The model improves tool use, code generation, and reasoning efficiency, achieving performance comparable to DeepSeek-R1 on difficult benchmarks while responding more quickly. It supports structured tool calling, code agents, and search agents, making it suitable for research, coding, and agentic workflows.
Key Specifications
Supported Parameters
This model supports the following parameters:
Features
This model supports the following features:
Performance Summary
DeepSeek-V3.1 Terminus, an update to DeepSeek-V3.1, demonstrates strong overall performance, particularly in reliability and specific accuracy benchmarks. It performs among the fastest models, ranking in the 67th percentile for speed across seven benchmarks, and offers competitive pricing, placing in the 46th percentile. Notably, the model exhibits exceptional reliability with a 100% success rate, indicating consistent and stable operation without technical failures. The model excels in critical areas, achieving perfect 100% accuracy in both Hallucinations (Baseline) and Ethics (Baseline) benchmarks, highlighting its ability to acknowledge uncertainty and adhere to ethical principles. It also shows robust performance in General Knowledge (99.5% accuracy) and Reasoning (90.0% accuracy), placing it in the 79th and 81st percentiles respectively. Its coding capabilities are strong, with 90.0% accuracy in the Coding (Baseline) benchmark. While its Email Classification accuracy (97.0%) is solid, it ranks in the 46th percentile, suggesting some room for improvement compared to top performers in this specific category. The model's hybrid reasoning architecture and optimized long-context training contribute to its efficiency in tool use, code generation, and agentic workflows.
Model Pricing
Current Pricing
| Feature | Price (per 1M tokens) |
|---|---|
| Prompt | $0.21 |
| Completion | $0.79 |
| Input Cache Read | $0.168 |
Price History
Available Endpoints
| Provider | Endpoint Name | Context Length | Pricing (Input) | Pricing (Output) |
|---|---|---|---|---|
|
DeepSeek
|
DeepSeek | deepseek/deepseek-v3.1-terminus | 131K | $0.21 / 1M tokens | $0.79 / 1M tokens |
|
Novita
|
Novita | deepseek/deepseek-v3.1-terminus | 131K | $0.21 / 1M tokens | $0.79 / 1M tokens |
|
AtlasCloud
|
AtlasCloud | deepseek/deepseek-v3.1-terminus | 131K | $0.21 / 1M tokens | $0.8 / 1M tokens |
|
DeepInfra
|
DeepInfra | deepseek/deepseek-v3.1-terminus | 163K | $0.21 / 1M tokens | $0.79 / 1M tokens |
|
Chutes
|
Chutes | deepseek/deepseek-v3.1-terminus | 163K | $0.23 / 1M tokens | $0.9 / 1M tokens |
|
SiliconFlow
|
SiliconFlow | deepseek/deepseek-v3.1-terminus | 163K | $0.27 / 1M tokens | $1 / 1M tokens |
|
SambaNova
|
SambaNova | deepseek/deepseek-v3.1-terminus | 131K | $3 / 1M tokens | $4.5 / 1M tokens |
|
Novita
|
Novita | deepseek/deepseek-v3.1-terminus | 131K | $0.216 / 1M tokens | $0.8 / 1M tokens |
Benchmark Results
| Benchmark | Category | Reasoning | Strategy | Free | Executions | Accuracy | Cost | Duration |
|---|
Other Models by deepseek
|
|
Released | Params | Context |
|
Speed | Ability | Cost |
|---|---|---|---|---|---|---|---|
| DeepSeek: DeepSeek V3.2 Speciale | Dec 01, 2025 | — | 131K |
Text input
Text output
|
★ | ★★★★★ | $$$$ |
| DeepSeek: DeepSeek V3.2 | Dec 01, 2025 | — | 131K |
Text input
Text output
|
— | — | $$$ |
| DeepSeek: DeepSeek V3.2 Exp | Sep 29, 2025 | — | 131K |
Text input
Text output
|
★★★ | ★★★★★ | $$$ |
| DeepSeek: DeepSeek V3.1 Terminus (exacto) | Sep 22, 2025 | ~671B | 131K |
Text input
Text output
|
— | — | $$$ |
| DeepSeek: DeepSeek V3.1 | Aug 21, 2025 | ~671B | 131K |
Text input
Text output
|
★★ | ★★★★ | $$$ |
| DeepSeek: DeepSeek V3.1 Base Unavailable | Aug 20, 2025 | ~671B | 163K |
Text input
Text output
|
★ | ★ | $$ |
| DeepSeek: R1 Distill Qwen 7B Unavailable | May 30, 2025 | 7B | 131K |
Text input
Text output
|
★ | ★ | $$$$ |
| DeepSeek: DeepSeek R1 0528 Qwen3 8B | May 29, 2025 | 8B | 131K |
Text input
Text output
|
★★★ | ★★★ | $$ |
| DeepSeek: R1 0528 | May 28, 2025 | ~671B | 128K |
Text input
Text output
|
★★★ | ★★★ | $$$ |
| DeepSeek: DeepSeek Prover V2 | Apr 30, 2025 | ~671B | 131K |
Text input
Text output
|
★★ | ★★★★ | $$$$ |
| DeepSeek: DeepSeek V3 Base Unavailable | Mar 29, 2025 | ~671B | 163K |
Text input
Text output
|
★ | ★ | $$$ |
| DeepSeek: DeepSeek V3 0324 | Mar 24, 2025 | ~685B | 163K |
Text input
Text output
|
★★★★ | ★★★★★ | $$ |
| DeepSeek: R1 Distill Llama 8B Unavailable | Feb 07, 2025 | 8B | 32K |
Text input
Text output
|
★ | ★★ | $$ |
| DeepSeek: R1 Distill Qwen 1.5B Unavailable | Jan 31, 2025 | 5B | 131K |
Text input
Text output
|
★★★ | ★ | $$$ |
| DeepSeek: R1 Distill Qwen 32B | Jan 29, 2025 | 32B | 131K |
Text input
Text output
|
★ | ★★★★ | $$$ |
| DeepSeek: R1 Distill Qwen 14B | Jan 29, 2025 | 14B | 32K |
Text input
Text output
|
★ | ★★ | $$$ |
| DeepSeek: R1 Distill Llama 70B | Jan 23, 2025 | 70B | 131K |
Text input
Text output
|
★★★ | ★★★★★ | $$ |
| DeepSeek: R1 | Jan 20, 2025 | ~671B | 128K |
Text input
Text output
|
★★★ | ★★★★ | $$$ |
| DeepSeek: DeepSeek V3 | Dec 26, 2024 | — | 163K |
Text input
Text output
|
★★★ | ★★★★ | $$$ |