Raises estimated decode speed by about 86%.
Adds memory headroom for longer context windows and future model growth.
~$219 MSRP
HelpingAI2 6B i1 needs ~6.1 GB VRAM. RX 580 8GB has 8.0 GB. With Q4_K_M quantization, expect ~30 tok/s.
Operating mode
Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
Select quantization to explore
Fit status
Runs well
Decode
30.1 tok/s
TTFT
6437 ms
Safe context
60K
Memory
6.1 GB / 8.0 GB
This setup is broadly balanced for this model.
Older PCIe generation
PCIe 3.0 is workable, but it compounds the penalty when you offload heavily or try to scale across multiple cards.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | C | Runs well | 30.1 tok/s | 3511 ms | 60K |
| Coding | C | Runs well | 30.1 tok/s | 6437 ms | 60K |
| Agentic Coding | C | Tight fit | 30.1 tok/s | 9363 ms | 60K |
| Reasoning | C | Runs well | 30.1 tok/s | 7607 ms | 60K |
| RAG | C | Tight fit | 30.1 tok/s | 11703 ms | 60K |
How HelpingAI2 6B i1 (6B params) fits at each quantization level on RX 580 8GB (8.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.3 GB | Low | C52 |
Q3_K_S | 3 | 2.9 GB | Low | C53 |
NVFP4 | 4 |
Copy-paste commands to run HelpingAI2 6B i1 on your machine.
Run
lms load hf-mradermacher--helpingai2-6b-i1-gguf && lms server startUpgrade options
Raises estimated decode speed by about 86%.
Adds memory headroom for longer context windows and future model growth.
~$219 MSRP
Raises estimated decode speed by about 279%.
Adds memory headroom for longer context windows and future model growth.
~$549 MSRP
Yes, RX 580 8GB can run HelpingAI2 6B i1 with a C grade (Runs well). Expected decode speed: 30.1 tok/s.
HelpingAI2 6B i1 (6B parameters) requires approximately 6.1 GB of memory with Q4_K_M quantization.
The recommended quantization for HelpingAI2 6B i1 is Q4_K_M, which balances quality and memory efficiency.
On RX 580 8GB, HelpingAI2 6B i1 achieves approximately 30.1 tokens per second decode speed with a time-to-first-token of 6437ms using Q4_K_M quantization.
For coding workloads, HelpingAI2 6B i1 on RX 580 8GB receives a C grade with 30.1 tok/s and 60K context.
On RX 580 8GB, HelpingAI2 6B i1 can safely use up to 60K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/hf-mradermacher--helpingai2-6b-i1-gguf-on-rx-580-8gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
| Medium |
| C53 |
Q4_K_M | 4 | 3.7 GB | Medium | C53 |
Q5_K_M | 5 | 4.3 GB | High | C53 |
Q6_KBest for your GPU | 6 | 4.9 GB | High | C52 |
Q8_0 | 8 | 6.4 GB | Very High | F0 |
F16 | 16 | 12.3 GB | Maximum | F0 |