Model benchmarks
/home/polaris/models/Tiel-Coder-35B-A3B-MTP-UD-Q6_K_XL.gguf local LLM performance
As of August 2026, /home/polaris/models/Tiel-Coder-35B-A3B-MTP-UD-Q6_K_XL.gguf runs at up to 36.1 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).
Model size
35B
Peak speed
36.1 tok/s
Average speed
35.6 tok/s
Min memory
17.1 GB
Max context
85,248 tokens
Avg output / run
28,982 tokens
Avg runtime / run
13m 13s
Avg quality
86.7
Benchmark runs
2
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 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 | 85.9 | 86.7 | 87.5 |
| Agent Workflow | 90.6 | 91.1 | 91.5 |
| Code Generation | 83.4 | 84.9 | 86.5 |
| Role Play & Narrative | 80.0 | 85.3 | 90.5 |
| Research & Analysis | 84.7 | 85.5 | 86.3 |
Performance by hardware and tool
Every hardware/tool/quantization combination /home/polaris/models/Tiel-Coder-35B-A3B-MTP-UD-Q6_K_XL.gguf has been benchmarked on, ranked by peak token generation speed. Last updated August 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| AMD Radeon RX 5600 OEM/5600 XT / 5700/5700 XT | llama.cpp | Q6_K | 36.1 tok/s | 35.6 tok/s | 17.1 GB | 85,248 tokens | 86.7 | 2 |
Frequently asked questions
- Is /home/polaris/models/Tiel-Coder-35B-A3B-MTP-UD-Q6_K_XL.gguf good for coding?
- In our benchmarks, /home/polaris/models/Tiel-Coder-35B-A3B-MTP-UD-Q6_K_XL.gguf scores 84.9/100 for coding, currently the best-scoring model for coding that runs on consumer hardware (≤24 GB VRAM). It runs at about 35.6 tok/s, so if you want more speed, Ornith-1.5-35B-A3B-oQ4e-mtp is faster (~111.8 tok/s) and still scores well for coding (81.8/100).
- Is /home/polaris/models/Tiel-Coder-35B-A3B-MTP-UD-Q6_K_XL.gguf good for agentic (tool-using) tasks?
- In our benchmarks, /home/polaris/models/Tiel-Coder-35B-A3B-MTP-UD-Q6_K_XL.gguf scores 91.1/100 for agentic workflows, among the top 2 for agentic workflows on consumer hardware (≤24 GB VRAM). It runs at about 35.6 tok/s, so if you want more speed, openai/gpt-oss-20b:2 is faster (~154.8 tok/s) and still scores well for agentic workflows (87.2/100).
- How fast is /home/polaris/models/Tiel-Coder-35B-A3B-MTP-UD-Q6_K_XL.gguf for local inference?
- Across 2 community benchmark runs, /home/polaris/models/Tiel-Coder-35B-A3B-MTP-UD-Q6_K_XL.gguf reaches up to 36.1 tok/s and averages 35.6 tok/s, with the fastest results on AMD Radeon RX 5600 OEM/5600 XT / 5700/5700 XT.
- How much memory does /home/polaris/models/Tiel-Coder-35B-A3B-MTP-UD-Q6_K_XL.gguf need?
- The leanest observed configuration used about 17.1 GB of memory (quantizations tested: Q6_K).
- Which tools have been used to run /home/polaris/models/Tiel-Coder-35B-A3B-MTP-UD-Q6_K_XL.gguf?
- Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.