RX 9060 XT 16GBBudget pick
16 GB VRAM (+8)320 GB/s (+64)
C
Raises estimated decode speed by about 58%.41.3 tok/s decode
Raises estimated decode speed by about 58%.
Adds memory headroom for longer context windows and future model growth.
~$349 MSRP
internlm3 8b instruct abliterated i1 needs ~7.5 GB VRAM. RX 6600 XT 8GB has 8.0 GB. With Q4_K_M quantization, expect ~26 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
Tight fit
Decode
26.2 tok/s
TTFT
7381 ms
Safe context
24K
Memory
7.5 GB / 8.0 GB
This setup is broadly balanced for this model.
Very little memory headroom
You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.
Buy headroom, not only minimum fit
A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | C | Tight fit | 26.2 tok/s | 4026 ms | 24K |
| Coding | C | Tight fit | 26.2 tok/s | 7381 ms | 24K |
| Agentic Coding | D | Runs with offload (needs ~0.3 GB host RAM) | 17.5 tok/s | 16082 ms | 24K |
| Reasoning | C | Tight fit | 26.2 tok/s | 8723 ms | 24K |
| RAG | D | Runs with offload (needs ~0.3 GB host RAM) | 17.5 tok/s | 20103 ms |
How internlm3 8b instruct abliterated i1 (8B params) fits at each quantization level on RX 6600 XT 8GB (8.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.1 GB | Low | C53 |
Q3_K_S | 3 | 3.9 GB | Low | C53 |
NVFP4 | 4 |
Copy-paste commands to run internlm3 8b instruct abliterated i1 on your machine.
Run
lms load hf-mradermacher--internlm3-8b-instruct-abliterated-i1-gguf && lms server startUpgrade options
Raises estimated decode speed by about 58%.
Adds memory headroom for longer context windows and future model growth.
~$349 MSRP
Raises estimated decode speed by about 103%.
Adds memory headroom for longer context windows and future model growth.
~$449 MSRP
Raises estimated decode speed by about 56%.
Adds memory headroom for longer context windows and future model growth.
~$479 MSRP
Yes, RX 6600 XT 8GB can run internlm3 8b instruct abliterated i1 with a C grade (Tight fit). Expected decode speed: 26.2 tok/s.
internlm3 8b instruct abliterated i1 (8B parameters) requires approximately 7.5 GB of memory with Q4_K_M quantization.
The recommended quantization for internlm3 8b instruct abliterated i1 is Q4_K_M, which balances quality and memory efficiency.
On RX 6600 XT 8GB, internlm3 8b instruct abliterated i1 achieves approximately 26.2 tokens per second decode speed with a time-to-first-token of 7381ms using Q4_K_M quantization.
For coding workloads, internlm3 8b instruct abliterated i1 on RX 6600 XT 8GB receives a C grade with 26.2 tok/s and 24K context.
On RX 6600 XT 8GB, internlm3 8b instruct abliterated i1 can safely use up to 24K 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--internlm3-8b-instruct-abliterated-i1-gguf-on-rx-6600-xt-8gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
| 24K |
4.5 GB |
| Medium |
| C53 |
Q4_K_MBest for your GPU | 4 | 4.9 GB | Medium | C52 |
Q5_K_M | 5 | 5.8 GB | High | F0 |
Q6_K | 6 | 6.6 GB | High | F0 |
Q8_0 | 8 | 8.6 GB | Very High | F0 |
F16 | 16 | 16.4 GB | Maximum | F0 |
Buy headroom, not only minimum fit. A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.