Which local LLMs can the DDR5-6000 dual-channel CPU run?
CPU-only inference with 4 GB of RAM kept for the OS, 8k context and an f16 KV cache. Verdicts are shown for each RAM size.
Specs
- Memory options
- 16 GB · 32 GB · 64 GB · 96 GB
- Memory bandwidth
- 96.0 GB/s
- Launch year
- 2022
Verdicts at a glance
At Q4_K_M (or the closest available quant) with 8k context.
- 16 GBRuns great0 modelsRuns well0 modelsRuns slowly13 modelsWon't run16 models3 more models run at a lower quant.
- 32 GBRuns great0 modelsRuns well0 modelsRuns slowly21 modelsWon't run8 models1 more model runs at a lower quant.
- 64 GBRuns great0 modelsRuns well0 modelsRuns slowly21 modelsWon't run8 models3 more models run at a lower quant.
- 96 GBRuns great0 modelsRuns well0 modelsRuns slowly24 modelsWon't run5 models1 more model runs at a lower quant.
How to read the verdicts
- Runs great
- Fully on the GPU at 20 tok/s or more
- Runs well
- Fully on the GPU at 8–20 tok/s; MoE experts in system RAM at 20 tok/s or more; or at least 90% on the GPU at 8 tok/s or more
- Runs slowly
- 2–8 tok/s; CPU-only; less than 90% on the GPU; or MoE experts in system RAM below 20 tok/s
- Won't run
- Does not fit, or under 2 tok/s
Every model on the DDR5-6000 dual-channel CPU
Scroll sideways to see every column.
| Model | Verdict | Speed | Quant | Memory | Runs as | Context | Notes |
|---|---|---|---|---|---|---|---|
| EXAONE 4.0 1.2B | Runs slowly | est. 36.5 tok/s29.2–43.9calibrated estimate ±20% | Q4_K_M | 1.3 GB RAM | CPU only | up to 64k |
|
| HyperCLOVA X SEED 1.5B | Runs slowly | est. 26.4 tok/s21.2–31.7calibrated estimate ±20% | Q4_K_M | 1.8 GB RAM | CPU only | up to 16k |
|
| Qwen3.5 35B-A3B | Runs slowly | est. 20.1 tok/s16.1–24.1calibrated estimate ±20% | Q4_K_M | 22.8 GB RAM | CPU only | up to 256k |
|
| gpt-oss-20b | Runs slowly | est. 18.0 tok/s14.4–21.7calibrated estimate ±20% | MXFP4 | 12.3 GB RAM | CPU only | up to 128k |
|
| Qwen3 30B-A3B (2507) | Runs slowly | est. 14.7 tok/s11.7–17.6calibrated estimate ±20% | Q4_K_M | 19.4 GB RAM | CPU only | up to 128k |
|
| Gemma 4 26B-A4B | Runs slowly | est. 14.3 tok/s11.4–17.1calibrated estimate ±20% | Q4_K_M | 17.3 GB RAM | CPU only | up to 256k |
|
| Kanana 1.5 15.7B-A3B | Runs slowly | est. 13.5 tok/s10.8–16.1calibrated estimate ±20% | Q4_K_M | 11.5 GB RAM | CPU only | up to 32k |
|
| gpt-oss-120b | Runs slowly | est. 13.4 tok/s10.8–16.1calibrated estimate ±20% | MXFP4 | 63.7 GB RAM | CPU only | up to 128k |
|
| DeepSeek R1 Distill Llama 8B | Runs slowly | est. 8.0 tok/s6.4–9.6calibrated estimate ±20% | Q4_K_M | 6.0 GB RAM | CPU only | up to 64k |
|
| Kanana 1.5 8B | Runs slowly | est. 8.0 tok/s6.4–9.6calibrated estimate ±20% | Q4_K_M | 6.0 GB RAM | CPU only | up to 32k |
|
| Llama 3.1 8B | Runs slowly | est. 8.0 tok/s6.4–9.6calibrated estimate ±20% | Q4_K_M | 6.0 GB RAM | CPU only | up to 128k |
|
| Qwen3.5 9B | Runs slowly | est. 7.8 tok/s6.3–9.4calibrated estimate ±20% | Q4_K_M | 6.1 GB RAM | CPU only | up to 256k | — |
| Qwen3 8B | Runs slowly | est. 7.7 tok/s6.2–9.2calibrated estimate ±20% | Q4_K_M | 6.2 GB RAM | CPU only | up to 32k | — |
| Qwen3.5 122B-A10B | Runs slowly | est. 6.4 tok/s5.1–7.7calibrated estimate ±20% | Q4_K_M | 78.5 GB RAM | CPU only | up to 256k | — |
| Gemma 4 12B | Runs slowly | est. 6.3 tok/s5.0–7.5calibrated estimate ±20% | Q4_K_M | 7.7 GB RAM | CPU only | up to 128k | — |
| Gemma 3 12B | Runs slowly | est. 6.1 tok/s4.9–7.3calibrated estimate ±20% | Q4_K_M | 7.8 GB RAM | CPU only | up to 128k | — |
| HyperCLOVA X SEED Think 14B | Runs slowly | est. 4.7 tok/s3.3–6.1theoretical estimate ±30% | Q4_K_M | 10.2 GB RAM | CPU only | up to 32k |
|
| Solar Open 100B | Runs slowly | est. 4.6 tok/s3.7–5.6calibrated estimate ±20% | Q4_K_M | 63.9 GB RAM | CPU only | up to 64k | — |
| Qwen3 14B | Runs slowly | est. 4.6 tok/s3.7–5.6calibrated estimate ±20% | Q4_K_M | 10.3 GB RAM | CPU only | up to 32k | — |
| Phi-4 | Runs slowly | est. 4.5 tok/s3.6–5.4calibrated estimate ±20% | Q4_K_M | 10.7 GB RAM | CPU only | up to 16k |
|
| Mistral Small 3.2 24B | Runs slowly | est. 3.1 tok/s2.5–3.7calibrated estimate ±20% | Q4_K_M | 15.7 GB RAM | CPU only | up to 32k | — |
| Gemma 3 27B | Runs slowly | est. 2.8 tok/s2.2–3.3calibrated estimate ±20% | Q4_K_M | 17.2 GB RAM | CPU only | up to 64k | — |
| Qwen3.5 27B | Runs slowly | est. 2.7 tok/s2.2–3.3calibrated estimate ±20% | Q4_K_M | 17.6 GB RAM | CPU only | up to 64k | — |
| Qwen3 32B | Runs slowly | est. 2.2 tok/s1.8–2.6calibrated estimate ±20% | Q4_K_M | 21.9 GB RAM | CPU only | up to 8k | — |
| DeepSeek R1 Distill Qwen 32B | Won't runTry Q2_K (heavy quality loss): Runs slowly | est. 3.3 tok/s2.7–4.0calibrated estimate ±20% | Q2_K | 14.5 GB RAM | CPU only | up to 8k |
|
| EXAONE 4.0 32B | Won't run | est. 2.4 tok/s1.9–2.9calibrated estimate ±20% | Q4_K_M | 19.9 GB RAM | CPU only | — |
|
| EXAONE 4.5 33B | Won't run | est. 2.3 tok/s1.9–2.8calibrated estimate ±20% | Q4_K_M | 20.6 GB RAM | CPU only | — |
|
| Llama 3.3 70B | Won't run | est. 1.1 tok/s0.8–1.3calibrated estimate ±20% | Q4_K_M | 45.2 GB RAM | CPU only | — |
|
| Solar Open 2 250B | Won't run | — | IQ4_XS | needs 136.6 GB | — | — |
|
Reasoning models spend extra tokens thinking, so their speed thresholds are 1.5× stricter (30 / 12 / 3 tok/s).
Verdict by memory size
| Model | 16 GB | 32 GB | 64 GB | 96 GB |
|---|---|---|---|---|
| EXAONE 4.0 1.2B | Runs slowly | Runs slowly | Runs slowly | Runs slowly |
| HyperCLOVA X SEED 1.5B | Runs slowly | Runs slowly | Runs slowly | Runs slowly |
| Qwen3.5 35B-A3B | Won't run | Runs slowly | Runs slowly | Runs slowly |
| gpt-oss-20b | Won't run | Runs slowly | Runs slowly | Runs slowly |
| Qwen3 30B-A3B (2507) | Won't run | Runs slowly | Runs slowly | Runs slowly |
| Gemma 4 26B-A4B | Won't run | Runs slowly | Runs slowly | Runs slowly |
| Kanana 1.5 15.7B-A3B | Runs slowly | Runs slowly | Runs slowly | Runs slowly |
| gpt-oss-120b | Won't run | Won't run | Won't run | Runs slowly |
| DeepSeek R1 Distill Llama 8B | Runs slowly | Runs slowly | Runs slowly | Runs slowly |
| Kanana 1.5 8B | Runs slowly | Runs slowly | Runs slowly | Runs slowly |
| Llama 3.1 8B | Runs slowly | Runs slowly | Runs slowly | Runs slowly |
| Qwen3.5 9B | Runs slowly | Runs slowly | Runs slowly | Runs slowly |
| Qwen3 8B | Runs slowly | Runs slowly | Runs slowly | Runs slowly |
| Qwen3.5 122B-A10B | Won't run | Won't run | Won't run | Runs slowly |
| Gemma 4 12B | Runs slowly | Runs slowly | Runs slowly | Runs slowly |
| Gemma 3 12B | Runs slowly | Runs slowly | Runs slowly | Runs slowly |
| HyperCLOVA X SEED Think 14B | Runs slowly | Runs slowly | Runs slowly | Runs slowly |
| Solar Open 100B | Won't run | Won't run | Won't run | Runs slowly |
| Qwen3 14B | Runs slowly | Runs slowly | Runs slowly | Runs slowly |
| Phi-4 | Runs slowly | Runs slowly | Runs slowly | Runs slowly |
| Mistral Small 3.2 24B | Won't run | Runs slowly | Runs slowly | Runs slowly |
| Gemma 3 27B | Won't run | Runs slowly | Runs slowly | Runs slowly |
| Qwen3.5 27B | Won't run | Runs slowly | Runs slowly | Runs slowly |
| Qwen3 32B | Won't run | Runs slowly | Runs slowly | Runs slowly |
| DeepSeek R1 Distill Qwen 32B | Won't run | Won't run | Won't run | Won't run |
| EXAONE 4.0 32B | Won't run | Won't run | Won't run | Won't run |
| EXAONE 4.5 33B | Won't run | Won't run | Won't run | Won't run |
| Llama 3.3 70B | Won't run | Won't run | Won't run | Won't run |
| Solar Open 2 250B | Won't run | Won't run | Won't run | Won't run |
Measured results on the DDR5-6000 dual-channel CPU
No public measurements for this device yet.
Frequently asked questions
What is the largest model this CPU setup can run?
Qwen3.5 122B-A10B at Q4_K_M (a 78.26 GB file) runs from 96 GB of RAM at est. 6.4 tok/s (5.1–7.7, calibrated estimate ±20%).
How many local LLMs run well on the DDR5-6000 dual-channel CPU?
At Q4_K_M with 8k context, with 96 GB of memory, out of 29 tracked models: 0 run great, 0 run well, 24 run slowly and 5 won't run.
Can the DDR5-6000 dual-channel CPU run a 70B model like Llama 3.3 70B?
It fits in memory but is too slow to use: est. 1.1 tok/s (0.8–1.3, calibrated estimate ±20%).
Speeds are estimates from memory bandwidth, calibrated against public benchmarks, and each one comes with an error band and a confidence label. Real results vary with drivers, backend, context length and thermals.