Hardware › NVIDIA CMP 170HX

NVIDIA CMP 170HX for local LLMs and RAG: 64GB, with big caveats

A former crypto-mining card built on the A100's GA100 chip. A community driver patch unlocks 64GB of fast HBM2e. Here is what it means for private document Q&A, and what can go wrong.

Verdict Specs For RAG Speeds Setup Cooling Before you buy Compare

Verdict

Most people should skip it for now. Unlocked, it gives you 64GB on one card with bandwidth above an RTX 3090, and LTT Labs measured about 80% of an RTX 3090 Ti's llama.cpp generation speed. But in October 2026 it costs about $3,400 with no returns. The unlock is a Linux-only driver patch, PCIe stays slow, and owners have reported cards dying.

Consider it if you run Linux, are comfortable patching drivers and building a fan duct, need one big memory pool for a 27–32B model at Q8 or gpt-oss-120B, and can absorb losing a card. Otherwise, a used RTX 3090 (about $1,522 sold) is the safer buy for most local RAG, or see the DGX Spark for 128GB with official support.

Spec box

GA100, 7nmSame chip family as the A100. Compute capability 8.0

64GB HBM2e8GB card, after unlock. 10GB card unlocks to 40GB

~1.49 TB/sMemory bandwidth, 8GB card (4096-bit)

250W TDPIdle about 30–40W. One 8-pin EPS plug

PassiveNo fans, no display outputs

PCIe Gen1 x4 stockGen2 after unlock. x16 needs soldering

No NVLinkFused off. Multi-card goes over PCIe

$4,299 launch2021 mining-card MSRP

Spec	Detail
Chip	GA100, 7nm, 70 SMs (74 reported with a newer cmpunlocker commit), 4,480 CUDA cores, 280 tensor cores, compute capability 8.0
Memory	8GB card: HBM2e, 4096-bit, ~1.49 TB/s, unlocks to 64GB. 10GB card: 5120-bit, ~1.56 TB/s, unlocks to 40GB (an 80GB setting was rejected as unstable)
Compute (stock)	Throttled: FP32 ~0.39–0.41 TFLOPS, INT8 1.64 TOPS. FP16 ~49 TFLOPS is not throttled. Disabling FMA gives ~6.2 TFLOPS FP32 (arXiv, niconiconi)
Compute (unlocked)	FP32 ~12–13 TFLOPS, INT8 ~48 TOPS (cmpunlocker)
PCIe	Stock Gen1 x4 (0.85 GB/s measured). Gen2 after unlock. Full x16 needs 12 lanes of 0402 capacitors soldered on. Gen3 is "work in progress"
Power	250W TDP, one 8-pin EPS (CPU-style) connector. A 300W VBIOS cross-flash exists but adds risk
Cooling / outputs	Passive heatsink, needs forced airflow. No display outputs
Launch price	$4,299 (2021)

Sources: 170th Street spec sheet, it-still-boots docs, cmpunlocker. Out of the box the card is heavily throttled. The 64GB, the compute figures, and the speeds below all assume the unlock.

What it means for local RAG

Memory is the point. 64GB holds a 27–32B model at Q8 with room for a long context, or gpt-oss-120B on one card (u/m94301 reports 78 t/s, source). You can also keep an embedding model and a reranker on the same card.
Prompt processing is decent. RAG prompts are long because they carry retrieved chunks. LTT Labs measured about 900 t/s prompt processing on a 27B model. By rough math, an 8,000-token prompt takes around 9 seconds before the first word. That is our arithmetic, not a measurement, and longer prompts usually run slower.
Slow PCIe mostly hurts loading. LTT measured 11s to load Qwen3.6 27B at Gen2 x4, against 6s at x16 and 6s on a 3090 Ti. Once the model is loaded, generation barely touches the bus. Swapping models often will feel slow.
No display outputs. You need a CPU with integrated graphics or a second GPU for a screen.
Multi-card is possible but rough. NVLink is fused off. Two-card vLLM needed P2P patches (gist).

Reported speeds

Tokens per second, single unlocked card, llama.cpp unless noted. Each row links to its source. These are Community report numbers: someone else ran them, not RAGShelf.

Model	Generation (t/s)	Prompt (t/s)	Comparison / notes	Setup	Source
Granite 4.1 8B Q4_K_M	113	2994	3090 Ti: 136 t/s. A locked (stock) card ran 30 t/s	LTT Labs, unlocked, llama.cpp	LTT Labs Community report
Qwen3.6 27B Q4_K_M	38	907	3090 Ti: 47 t/s	LTT Labs, unlocked, llama.cpp	LTT Labs Community report
Qwen3.8 27B Q8_0	33	897	Two 3090 Tis: 31 t/s (layer split) / 48 t/s (tensor split)	LTT Labs, unlocked, llama.cpp	LTT Labs Community report
gpt-oss-20B	120	2000		u/m94301, Gen2 x4, llama.cpp	r/LocalLLaMA, Aug 11, 2026 Community report
gpt-oss-120B	78	1244		u/m94301, Gen2 x4, llama.cpp	r/LocalLLaMA, Aug 11, 2026 Community report
Qwen3.6-27B Q5_K_M	29 (47 with MTP)	812		u/m94301, Gen2 x4, llama.cpp	r/LocalLLaMA, Aug 11, 2026 Community report
gemma-4-31B Q8_0	23	767		u/m94301, Gen2 x4, llama.cpp	r/LocalLLaMA, Aug 11, 2026 Community report
Mistral-Medium 128B dense	9.8	not quoted	Two cards	u/m94301, llama.cpp	r/LocalLLaMA, Aug 11, 2026 Community report

LTT Labs prompt figures are pp512. We left out numbers from aggregator sites that don't show their testing.

Software support

Engine / OS	Status	Notes
llama.cpp	Works Community report	Used for nearly every published number (LTT Labs, Reddit)
vLLM	Works Community report	Reported on vLLM 0.30 with two cards and P2P patches on an EPYC board (gist)
Ollama	Unconfirmed	We found no report either way. Ollama's GPU docs list compute capability 5.0+ as supported, and the card is 8.0, but the unlock needs a pinned driver. Treat it as unknown
ExLlamaV3	Unverified	No published test we could check
Windows	Likely 8GB only, single source	The unlock is Linux-only. One source says Windows sees only 8GB (VRAMGlass). We have not seen a second report

Setup

These are the steps owners describe. Follow the cmpunlocker README for exact commands. It changes often.

Linux on x86-64 only. Turn Secure Boot off. You need root.
Install the pinned driver: nvidia-open 610.43.02 or 610.43.03 (forks also support 610.57.04). Hold it so updates don't replace it.
Run cmpunlocker. It patches the driver, not the card's firmware. Re-run it after every kernel or driver update.
Check the result. Memory should read about 64GB (8GB card) or 40GB (10GB card), and the link should read Gen2.
Test the memory before you trust it. Run memtest_vulkan for about 2 hours (LTT Labs' guidance). Do this during any return or dispute window you have.
Build llama.cpp with CUDA and start with a small model, then scale up.

nvidia-smi --query-gpu=name,memory.total,pcie.link.gen.current,pcie.link.width.current,temperature.gpu,power.draw --format=csv

Cooling and power

It has no fans. In a desktop case it will overheat without forced airflow. About 80°C is treated as an emergency stop (air-cooling notes).
Use a fan duct. LTT Labs used a 3D-printed 120mm duct (Printables model).
Power: 250W TDP, about 30–40W idle. It takes one 8-pin EPS (CPU-style) plug, not a PCIe plug, so check your PSU cables or adapter. A 300W VBIOS cross-flash exists, but it adds heat and risk.

Before you buy

No returns, real failure reports. One owner says 2 of 5 cards died after 2 weeks and a third had defective tensor cores. They put fair value at "sub $1000" (r/LocalLLaMA, Sep 2, 2026). LTT Labs reports its loaner card failed (LTT Labs).

What	Price	Source	Date
Typical asking range	$2,800–5,000, median $3,399, +13.3% over 30 days	VRAMGlass	Oct 27, 2026
eBay listing (ships from Shenzhen)	$3,499.98, no returns, 76 sold	eBay listing	Oct 2026
eBay listing (US stock)	$3,799.03, no returns	eBay listing	Oct 2026
Price history	A few hundred dollars in June 2026, $1,300–1,600 in August, over $2,000 in September	LTT Labs	Sep 12, 2026

Prices as of October 2026 and rising. Listings and asking prices are not sale prices. Also see Llama Builds, Oct 19, 2026.

Get the 8GB card for 64GB. The 10GB version unlocks to only 40GB.
Windows will likely see only 8GB. That comes from a single source (VRAMGlass), but the unlock is Linux-only either way.
Ollama is unconfirmed and ExLlamaV3 is unverified. Plan on llama.cpp or vLLM.
Budget for a fan, a duct, and an EPS cable.

How it compares

Option	Memory	Bandwidth	Used price (Oct 2026)	Power / cooling	Catch
CMP 170HX (unlocked)	64GB HBM2e (8GB card)	~1.49 TB/s	~$3,399 median asking (VRAMGlass)	250W, passive	Linux-only unlock, pinned driver, slow PCIe, no returns, failure reports
RTX 3090 (used)	24GB GDDR6X	936 GB/s (TechPowerUp)	~$1,522 sold median (gpusold)	350W, fans	Works with everything, on Windows too. Needs 2–3 cards for 64GB
Tesla P40 (used)	24GB GDDR5	346 GB/s (TechPowerUp)	~$293 sold (gpusold), ~$351 asking (CresvaMent)	250W, passive	Old Pascal chip (compute 6.1). Cheap, slow, needs a fan duct too
Instinct MI50 (used)	16GB or 32GB HBM2	~1 TB/s (TechPowerUp)	~$226 (16GB) / ~$617 (32GB) sold (gpusold)	300W, passive	AMD card. Check your engine's ROCm or Vulkan support first
DGX Spark	128GB unified	273 GB/s	See our DGX Spark guide	Small desktop box	Official NVIDIA support and playbooks. Slower decode on dense models, no unlock needed

Used prices are from gpusold (sold medians) and CresvaMent (asking medians), checked Oct 26, 2026. For model picks per memory size, see Models.

Last checked Oct 26, 2026. Prices move fast on this card. Nothing on this page was tested by RAGShelf. Every speed is a community or press report, linked on its row.