Model benchmarks
speakleash/Bielik-11B-v3.0-Instruct-GGUF:Q5_K_M local LLM performance
As of October 2026, speakleash/Bielik-11B-v3.0-Instruct-GGUF:Q5_K_M runs at up to 60.1 tok/s for local inference (best of 5 community benchmark runs across 1 GPU).
Model size
11B
Peak speed
60.1 tok/s
Average speed
58.3 tok/s
Avg PP
1119.0 tok/s
Min memory
11.0 GB
Max context
32,768 tokens
Avg output / run
4,623 tokens
Avg runtime / run
1m 23s
Avg quality
55.1
Benchmark runs
5
GPUs tested
1
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 5 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 | 49.4 | 55.1 | 59.9 |
| Agent Workflow | 71.2 | 75.4 | 78.9 |
| Code Generation | 15.6 | 23.1 | 30.6 |
| Role Play & Narrative | 61.7 | 71.5 | 80.0 |
| Research & Analysis | 41.9 | 50.4 | 64.6 |
Performance by hardware and tool
Every hardware/tool/quantization combination speakleash/Bielik-11B-v3.0-Instruct-GGUF:Q5_K_M has been benchmarked on, ranked by peak token generation speed. Last updated October 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| AMD Radeon RX 9070/9070 XT/9070 GRE | llama.cpp | Q5_K_M | 60.1 tok/s | 58.3 tok/s | 11.0 GB | 32,768 tokens | 55.1 | 5 |
Benchmark runs
All 5 speakleash/Bielik-11B-v3.0-Instruct-GGUF:Q5_K_M runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is speakleash/Bielik-11B-v3.0-Instruct-GGUF:Q5_K_M good for coding?
- In our benchmarks, speakleash/Bielik-11B-v3.0-Instruct-GGUF:Q5_K_M scores 23.1/100 for coding. It runs at about 58.3 tok/s, so if you want more speed, Nex-N2.5-mini-IQ3_XXS is faster (~91.4 tok/s) and still scores well for coding (81.6/100).
- Is speakleash/Bielik-11B-v3.0-Instruct-GGUF:Q5_K_M good for agentic (tool-using) tasks?
- In our benchmarks, speakleash/Bielik-11B-v3.0-Instruct-GGUF:Q5_K_M scores 75.4/100 for agentic workflows. It runs at about 58.3 tok/s, so if you want more speed, Nex-N2.5-mini-APEX-Mini is faster (~88.2 tok/s) and still scores well for agentic workflows (91.3/100).
- How fast is speakleash/Bielik-11B-v3.0-Instruct-GGUF:Q5_K_M for local inference?
- Across 5 community benchmark runs, speakleash/Bielik-11B-v3.0-Instruct-GGUF:Q5_K_M reaches up to 60.1 tok/s and averages 58.3 tok/s, with the fastest results on AMD Radeon RX 9070/9070 XT/9070 GRE.
- How much memory does speakleash/Bielik-11B-v3.0-Instruct-GGUF:Q5_K_M need?
- The leanest observed configuration used about 11.0 GB of memory (quantizations tested: Q5_K_M).
- Which tools have been used to run speakleash/Bielik-11B-v3.0-Instruct-GGUF:Q5_K_M?
- Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.