HelpingAI2 6B needs ~6.5 GB VRAM. Radeon RX 6850M XT 12GB has 12.0 GB. With Q4_K_M quantization, expect ~66 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
66.1 tok/s
TTFT
2929 ms
Safe context
142K
Memory
6.5 GB / 12.0 GB
This setup is broadly balanced for this model.
No major red flags
This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | C | Runs well | 66.1 tok/s | 1598 ms | 142K |
| Coding | C | Runs well | 66.1 tok/s | 2929 ms | 142K |
| Agentic Coding | C | Runs well | 66.1 tok/s | 4260 ms | 142K |
| Reasoning | C | Runs well | 66.1 tok/s | 3462 ms | 142K |
| RAG | C | Runs well | 66.1 tok/s | 5325 ms | 142K |
Inference speed
Estimated decode speed (tokens/sec) for HelpingAI2 6B at Q4_K_M across popular GPUs and Apple Silicon, using the fastest local runtime per device. Fastest is RTX 5090 32GB at ~114 tok/s. Speed is memory-bandwidth bound, so cards that fit the whole model in VRAM run far faster than ones that offload to system RAM.
| GPU / Mac | Memory | Quant | Speed (tok/s) | Fits? |
|---|---|---|---|---|
| 32 GB | Q4_K_M | 114.0 | Fits | |
| 24 GB | Q4_K_M | 84.0 | Fits | |
| 16 GB | Q4_K_M | 84.0 | Fits | |
| 24 GB | Q4_K_M | 84.0 | Fits | |
| 12 GB | Q4_K_M | 84.0 | Fits | |
RX 7900 XTX 24GB | 24 GB | Q4_K_M | 84.0 | Fits |
MacBook Pro M4 Max 128GB | 128 GB | Q4_K_M | 84.0 | Fits |
Mac Studio M3 Ultra 256GB | 256 GB | Q4_K_M | 84.0 | Fits |
Mac Studio M2 Ultra 128GB | 128 GB | Q4_K_M | 84.0 | Fits |
Mac Studio M1 Ultra 128GB | 128 GB | Q4_K_M | 84.0 | Fits |
MacBook Pro M4 Max 64GB | 64 GB | Q4_K_M | 84.0 | Fits |
MacBook Pro M3 Max 64GB | 64 GB | Q4_K_M | 65.6 | Fits |
| 12 GB | Q4_K_M | 64.9 | Fits | |
MacBook Pro M1 Max 64GB | 64 GB | Q4_K_M | 60.1 | Fits |
| 8 GB | Q4_K_M | 54.3 | Fits | |
MacBook Pro M4 Pro 48GB | 48 GB | Q4_K_M | 52.8 | Fits |
Estimates for single-stream decoding at Q4_K_M; real tokens/sec varies with prompt length, context, batch size, and runtime build. Prompt processing (prefill) is faster than the decode figures shown here.
How HelpingAI2 6B (6B params) fits at each quantization level on Radeon RX 6850M XT 12GB (12.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.3 GB | Low | C48 |
Q3_K_S | 3 | 2.9 GB | Low | C49 |
NVFP4 | 4 | 3.4 GB | Medium | C49 |
Q4_K_M | 4 | 3.7 GB | Medium | C50 |
Q5_K_M | 5 | 4.3 GB | High | C51 |
Q6_K | 6 | 4.9 GB | High | C51 |
Q8_0Best for your GPU | 8 | 6.4 GB | Very High | C52 |
F16 | 16 | 12.3 GB | Maximum | F0 |
Copy-paste commands to run HelpingAI2 6B on your machine.
Run
lms load hf-helpingai--helpingai2-6b && lms server startYes, Radeon RX 6850M XT 12GB can run HelpingAI2 6B with a C grade (Runs well). Expected decode speed: 66.1 tok/s.
HelpingAI2 6B (6B parameters) requires approximately 6.5 GB of memory with Q4_K_M quantization.
The recommended quantization for HelpingAI2 6B is Q4_K_M, which balances quality and memory efficiency.
On Radeon RX 6850M XT 12GB, HelpingAI2 6B achieves approximately 66.1 tokens per second decode speed with a time-to-first-token of 2929ms using Q4_K_M quantization.
For coding workloads, HelpingAI2 6B on Radeon RX 6850M XT 12GB receives a C grade with 66.1 tok/s and 142K context.
On Radeon RX 6850M XT 12GB, HelpingAI2 6B can safely use up to 142K 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-helpingai--helpingai2-6b-on-rx-6850m-xt-12gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: