Model benchmarks
deepseek-r1:1.5b local LLM performance
As of September 2026, deepseek-r1:1.5b runs at up to 247.5 tok/s for local inference (best of 2 community benchmark runs across 2 GPUs).
Model size
1.8B
Peak speed
247.5 tok/s
Average speed
151.0 tok/s
Avg PP
6478.0 tok/s
Min memory
1.2 GB
Max context
8.192 tokens
Avg output / run
7.524 tokens
Avg runtime / run
1m 40s
Avg quality
8.7
Benchmark runs
2
GPUs tested
2
Quality by task
Average LLM-judged quality (0–100) with the run-to-run spread shown as a P5–P95 band, overall and for each benchmark task, across all 2 runs. The low and high columns show how much the judge’s score varies between runs, and need at least two runs to display.
| Task | P5 (low) | Avg | P95 (high) |
|---|---|---|---|
| Overall | 7.8 | 8.7 | 9.6 |
| Agent Workflow | 11.4 | 16.7 | 22.0 |
| Code Generation | 0.1 | 1.5 | 2.8 |
| Role Play & Narrative | 3.2 | 3.3 | 3.4 |
| Research & Analysis | 13.1 | 13.3 | 13.6 |
Performance by hardware and tool
Every hardware/tool/quantization combination deepseek-r1:1.5b has been benchmarked on, ranked by peak token generation speed. Last updated September 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| NVIDIA GeForce RTX 3060 Ti | Ollama | Q4_K_M | 247.5 tok/s | 247.5 tok/s | 1.3 GB | 8.192 tokens | 7.7 | 1 |
| NVIDIA GeForce RTX 2050 | Ollama | Q4_K_M | 54.5 tok/s | 54.5 tok/s | 1.2 GB | 8.192 tokens | 9.7 | 1 |
Benchmark runs
All 2 deepseek-r1:1.5b runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is deepseek-r1:1.5b good for agentic (tool-using) tasks?
- In our benchmarks, deepseek-r1:1.5b scores 16.7/100 for agentic workflows. It runs at about 151.0 tok/s, so if you want more speed, unsloth/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-GGUF:UD-Q4_K_XL is faster (~175.3 tok/s) and still scores well for agentic workflows (83.6/100).
- How fast is deepseek-r1:1.5b for local inference?
- Across 2 community benchmark runs, deepseek-r1:1.5b reaches up to 247.5 tok/s and averages 151.0 tok/s, with the fastest results on NVIDIA GeForce RTX 3060 Ti.
- How much memory does deepseek-r1:1.5b need?
- The leanest observed configuration used about 1.2 GB of memory (quantizations tested: Q4_K_M).
- Which tools have been used to run deepseek-r1:1.5b?
- Benchmarks were submitted using Ollama. Results are community-contributed and updated as new runs arrive.