What AI models can AMD Radeon RX 7600 run?

The AMD Radeon RX 7600 can run 59 AI models. Top performers include all-MiniLM-L6-v2, nomic-embed-text v1.5, Llama 3.2 1B Instruct. See the full compatibility table above for speeds and quality ratings.

Is AMD Radeon RX 7600 good for AI coding?

With 8 GB, the AMD Radeon RX 7600 has limited VRAM for AI coding workflows.

How much VRAM does AMD Radeon RX 7600 have?

The AMD Radeon RX 7600 has 8 GB of GDDR6 VRAM with 288 GB/s bandwidth.

Can AMD Radeon RX 7600 run 70B models?

70B models can run on the AMD Radeon RX 7600 with CPU offloading, but performance will be reduced. Consider a device with 48GB+ inference memory for full-speed 70B inference.

Is AMD Radeon RX 7600 worth it for AI?

At $239, the AMD Radeon RX 7600 offers 8 GB GDDR6 VRAM and runs 59 AI models. It works for smaller models and experimentation.

Desktop GPU

AMD Radeon RX 7600

8 GB GDDR6 · 288 GB/s

From

$239

Estimated street price

VRAM

8 GB

Bandwidth

288 GB/s

TDP

165W

Models

Tier

Limited

The AMD Radeon RX 7600 with 8 GB GDDR6 VRAM can handle 59 AI models across embedding, ai_building, coding. Best performance: all-MiniLM-L6-v2 at 500 tok/s (excellent). Current price: approximately $239.

Source: OwnRig methodology

VRAM

8 GB

Bandwidth

288 GB/s

Memory Type

GDDR6

TDP

165W

Form Factor

2-slot, 204mm

Builder Capability: Limited

Insufficient VRAM for most AI coding workflows.

Software

Inference Backends

The software stacks that matter most for real-world inference on this device.

ROCm

beta

Functional for supported workloads, but RDNA 3 consumer support still trails NVIDIA in tooling maturity.

Vulkan

stable

Preferred llama.cpp path for budget AMD cards with broad local runtime compatibility.

What it can run

59 models


all-MiniLM-L6-v2	FP16	500 tok/s	Excellent
Arcee Trinity Nano 6B	Q8_0	51 tok/s	Excellent
Code Llama 34B Instruct	Q2_K	2 tok/s	Marginal
Codestral 22B	Q3_K_M	2 tok/s	Marginal
Command R 35B	Q3_K_M	2 tok/s	Marginal
DeepSeek Coder V2 Lite 16B	Q3_K_M	10 tok/s	Marginal
DeepSeek R1	Q2_K	–	Not viable
DeepSeek R1 Distill Qwen 32B	Q3_K_M	2 tok/s	Marginal
DeepSeek R1 Distill Qwen 7B	Q4_K_M	25 tok/s	Acceptable
DeepSeek V3	Q2_K	–	Not viable
FLUX.1 Dev	Q4_K_M	2 tok/s	Marginal
Gemma 2 27B Instruct	Q2_K	2 tok/s	Marginal
Gemma 2 9B Instruct	Q4_K_M	22 tok/s	Acceptable
Gemma 3 12B	Q3_K_M	14 tok/s	Marginal
Gemma 3 27B	Q3_K_M	2 tok/s	Marginal
Gemma 3 4B	Q5_K_M	43 tok/s	Good
Gemma 4 E2B	Q8_0	43 tok/s	Good
Gemma 4 E4B	Q6_K	34 tok/s	Good
GigaChat Lightning 10B	Q4_K_M	50 tok/s	Acceptable
InternLM 2.5 7B Chat	Q4_K_M	23 tok/s	Acceptable
Llama 3.1 70B Instruct	Q2_K	–	Not viable
Llama 3.1 8B Instruct	Q4_K_M	25 tok/s	Acceptable
Llama 3.2 11B Vision	Q3_K_M	–	Marginal
Llama 3.2 1B Instruct	Q8_0	74 tok/s	Good
Llama 3.2 3B Instruct	Q8_0	51 tok/s	Good
Llama 3.3 70B Instruct	Q3_K_M	–	Not viable
Llama 4 Scout	Q3_K_M	–	Not viable
LLaVA 1.6 13B	Q3_K_M	17 tok/s	Marginal
Mistral 7B Instruct v0.3	Q4_K_M	24 tok/s	Acceptable
Mistral Large 2 123B	Q2_K	–	Not viable
Mistral Small 24B Instruct	Q3_K_M	2 tok/s	Marginal
Mixtral 8x7B Instruct	Q2_K	–	Not viable
nomic-embed-text v1.5	Q8_0	500 tok/s	Good
NVIDIA Nemotron-3-super-120B-A12B	Q2_K	–	Not viable
Phi-3 Medium 14B Instruct	Q3_K_M	5 tok/s	Marginal
Phi-3 Mini 3.8B Instruct	Q5_K_M	41 tok/s	Good
Phi-4 14B	Q3_K_M	4 tok/s	Marginal
Phi-4 Mini	Q5_K_M	43 tok/s	Good
Qwen 2.5 14B Instruct	Q3_K_M	4 tok/s	Marginal
Qwen 2.5 72B Instruct	Q2_K	–	Not viable
Qwen 2.5 7B Instruct	Q4_K_M	23 tok/s	Acceptable
Qwen 2.5 Coder 32B Instruct	Q2_K	2 tok/s	Marginal
Qwen 2.5 Coder 7B Instruct	Q4_K_M	24 tok/s	Acceptable
Qwen3-14B Instruct	Q3_K_M	4 tok/s	Marginal
Qwen3-30B-A3B	Q3_K_M	2 tok/s	Marginal
Qwen3-32B Instruct	Q3_K_M	2 tok/s	Marginal
Qwen3-8B Instruct	Q5_K_M	19 tok/s	Acceptable
Qwen3.5-122B-A10B	Q3_K_M	–	Not viable
Qwen3.5-27B	Q3_K_M	2 tok/s	Marginal
Qwen3.5-397B (MoE)	Q2_K	–	Not viable
Qwen3.6-27B	Q3_K_M	–	Not viable
QwQ 32B Preview	Q2_K	2 tok/s	Marginal
Stable Diffusion 3 Medium	FP16	–	Acceptable
Stable Diffusion 3.5 Large	Q8_0	2 tok/s	Marginal
Stable Diffusion XL 1.0	FP16	–	Good
StarCoder 2 15B	Q3_K_M	4 tok/s	Marginal
Whisper Large V3	Q5_K_M	–	Excellent
Whisper Large V3 Turbo	FP16	–	Good
Yi 1.5 34B Chat	Q3_K_M	2 tok/s	Marginal

Showing 59 of 59 entries

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FAQ

Frequently Asked Questions

What AI models can AMD Radeon RX 7600 run?: The AMD Radeon RX 7600 can run 59 AI models. Top performers include all-MiniLM-L6-v2, nomic-embed-text v1.5, Llama 3.2 1B Instruct. See the full compatibility table above for speeds and quality ratings.
Is AMD Radeon RX 7600 good for AI coding?: With 8 GB, the AMD Radeon RX 7600 has limited VRAM for AI coding workflows.
How much VRAM does AMD Radeon RX 7600 have?: The AMD Radeon RX 7600 has 8 GB of GDDR6 VRAM with 288 GB/s bandwidth.
Can AMD Radeon RX 7600 run 70B models?: 70B models can run on the AMD Radeon RX 7600 with CPU offloading, but performance will be reduced. Consider a device with 48GB+ inference memory for full-speed 70B inference.
Is AMD Radeon RX 7600 worth it for AI?: At $239, the AMD Radeon RX 7600 offers 8 GB GDDR6 VRAM and runs 59 AI models. It works for smaller models and experimentation.

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