Quick Answer: RX 7600 offers 8GB VRAM and starts around $459.00. It delivers approximately 60 tokens/sec on deepseek-ai/DeepSeek-OCR-2. It typically draws 165W under load.
This GPU offers reliable throughput for local AI workloads. Pair it with the right model quantization to hit your desired tokens/sec, and monitor prices below to catch the best deal.
With 8GB VRAM, RX 7600 can run models up to approximately 20B parameters using 4-bit quantization. This is suitable for 7B-13B models like Llama 3 8B, Mistral 7B, and Qwen 7B.
Consider RTX 4070 or RTX 4080 — Significant performance increase for AI workloads.
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| Model | Quantization | Tokens/sec | VRAM used |
|---|---|---|---|
| deepseek-ai/DeepSeek-OCR-2 | Q4 | 59.53 tok/sEstimated Auto-generated benchmark | 2GB |
| google-t5/t5-3b | Q4 | 58.17 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-3.2-1B-Instruct | Q4 | 57.97 tok/sEstimated Auto-generated benchmark | 1GB |
| WeiboAI/VibeThinker-1.5B | Q4 | 57.89 tok/sEstimated Auto-generated benchmark | 1GB |
| unsloth/gemma-3-1b-it | Q4 | 57.82 tok/sEstimated Auto-generated benchmark | 1GB |
| deepseek-ai/deepseek-coder-1.3b-instruct | Q4 | 57.57 tok/sEstimated Auto-generated benchmark | 2GB |
| google-bert/bert-base-uncased | Q4 | 57.30 tok/sEstimated Auto-generated benchmark | 1GB |
| google/gemma-2-2b-it | Q4 | 57.19 tok/sEstimated Auto-generated benchmark | 1GB |
| deepseek-ai/DeepSeek-OCR | Q4 | 56.79 tok/sEstimated Auto-generated benchmark | 2GB |
| unsloth/Llama-3.2-3B-Instruct | Q4 | 56.47 tok/sEstimated Auto-generated benchmark | 2GB |
| Qwen/Qwen2.5-3B-Instruct | Q4 | 56.27 tok/sEstimated Auto-generated benchmark | 2GB |
| nineninesix/kani-tts-2-en | Q4 | 56.17 tok/sEstimated Auto-generated benchmark | 1GB |
| facebook/sam3 | Q4 | 56.11 tok/sEstimated Auto-generated benchmark | 1GB |
| tencent/HunyuanOCR | Q4 | 55.11 tok/sEstimated Auto-generated benchmark | 1GB |
| meta-llama/Llama-3.2-1B | Q4 | 54.73 tok/sEstimated Auto-generated benchmark | 1GB |
| Qwen/Qwen3-ASR-1.7B | Q4 | 54.22 tok/sEstimated Auto-generated benchmark | 2GB |
| context-labs/meta-llama-Llama-3.2-3B-Instruct-FP16 | Q4 | 54.15 tok/sEstimated Auto-generated benchmark | 2GB |
| allenai/OLMo-2-0425-1B | Q4 | 54.12 tok/sEstimated Auto-generated benchmark | 1GB |
| bigcode/starcoder2-3b | Q4 | 53.88 tok/sEstimated Auto-generated benchmark | 2GB |
| TinyLlama/TinyLlama-1.1B-Chat-v1.0 | Q4 | 53.73 tok/sEstimated Auto-generated benchmark | 1GB |
| meta-llama/Llama-3.2-3B-Instruct | Q4 | 53.48 tok/sEstimated Auto-generated benchmark | 2GB |
| google/gemma-3-1b-it | Q4 | 52.57 tok/sEstimated Auto-generated benchmark | 1GB |
| LiquidAI/LFM2-1.2B | Q4 | 52.46 tok/sEstimated Auto-generated benchmark | 1GB |
| Qwen/Qwen2.5-3B | Q4 | 51.86 tok/sEstimated Auto-generated benchmark | 2GB |
| nari-labs/Dia2-2B | Q4 | 51.39 tok/sEstimated Auto-generated benchmark | 2GB |
| google/embeddinggemma-300m | Q4 | 50.92 tok/sEstimated Auto-generated benchmark | 1GB |
| ibm-granite/granite-3.3-2b-instruct | Q4 | 49.97 tok/sEstimated Auto-generated benchmark | 1GB |
| google/gemma-2b | Q4 | 49.27 tok/sEstimated Auto-generated benchmark | 1GB |
| ibm-research/PowerMoE-3b | Q4 | 49.15 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-3.2-3B | Q4 | 49.03 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-Guard-3-1B | Q4 | 48.89 tok/sEstimated Auto-generated benchmark | 1GB |
| Qwen/Qwen2.5-7B-Instruct | Q4 | 48.56 tok/sEstimated Auto-generated benchmark | 4GB |
| ibm-granite/granite-docling-258M | Q4 | 48.53 tok/sEstimated Auto-generated benchmark | 4GB |
| zai-org/GLM-4.5-Air | Q4 | 48.42 tok/sEstimated Auto-generated benchmark | 4GB |
| unsloth/Llama-3.2-1B-Instruct | Q4 | 48.33 tok/sEstimated Auto-generated benchmark | 1GB |
| openai-community/gpt2 | Q4 | 48.29 tok/sEstimated Auto-generated benchmark | 4GB |
| bigscience/bloomz-560m | Q4 | 48.27 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen3-4B-Thinking-2507-FP8 | Q4 | 48.24 tok/sEstimated Auto-generated benchmark | 2GB |
| Qwen/Qwen3-0.6B | Q4 | 48.16 tok/sEstimated Auto-generated benchmark | 3GB |
| vikhyatk/moondream2 | Q4 | 48.11 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen2.5-1.5B-Instruct | Q4 | 48.04 tok/sEstimated Auto-generated benchmark | 3GB |
| Qwen/Qwen2.5-0.5B | Q4 | 48.01 tok/sEstimated Auto-generated benchmark | 3GB |
| black-forest-labs/FLUX.1-dev | Q4 | 47.99 tok/sEstimated Auto-generated benchmark | 4GB |
| lmstudio-community/DeepSeek-R1-0528-Qwen3-8B-MLX-8bit | Q4 | 47.96 tok/sEstimated Auto-generated benchmark | 4GB |
| sshleifer/tiny-gpt2 | Q4 | 47.95 tok/sEstimated Auto-generated benchmark | 4GB |
| ibm-granite/granite-3.3-8b-instruct | Q4 | 47.94 tok/sEstimated Auto-generated benchmark | 4GB |
| xgen-universe/Capybara | Q4 | 47.94 tok/sEstimated Auto-generated benchmark | 4GB |
| apple/OpenELM-1_1B-Instruct | Q4 | 47.94 tok/sEstimated Auto-generated benchmark | 1GB |
| inference-net/Schematron-3B | Q4 | 47.82 tok/sEstimated Auto-generated benchmark | 2GB |
| deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B | Q4 | 47.60 tok/sEstimated Auto-generated benchmark | 3GB |
Note: Performance estimates are calculated. Real results may vary. Methodology · Submit real data
| Model | Quantization | Verdict | Estimated speed | VRAM needed |
|---|---|---|---|---|
| openai-community/gpt2 | Q8 | Fits (tight) | 27.99 tok/sEstimated | 7GB (have 8GB) |
| openai-community/gpt2 | FP16 | Not supported | 15.51 tok/sEstimated | 15GB (have 8GB) |
| Qwen/Qwen2.5-7B-Instruct | Q4 | Fits comfortably | 48.56 tok/sEstimated | 4GB (have 8GB) |
| Qwen/Qwen2.5-7B-Instruct | Q8 | Fits (tight) | 32.84 tok/sEstimated | 7GB (have 8GB) |
| Qwen/Qwen2.5-7B-Instruct | FP16 | Not supported | 16.28 tok/sEstimated | 15GB (have 8GB) |
| Qwen/Qwen3-0.6B | Q4 | Fits comfortably | 48.16 tok/sEstimated | 3GB (have 8GB) |
| Qwen/Qwen3-0.6B | Q8 | Fits comfortably | 32.24 tok/sEstimated | 6GB (have 8GB) |
| Qwen/Qwen3-0.6B | FP16 | Not supported | 17.61 tok/sEstimated | 13GB (have 8GB) |
| Gensyn/Qwen2.5-0.5B-Instruct | Q4 | Fits comfortably | 41.52 tok/sEstimated | 3GB (have 8GB) |
| Gensyn/Qwen2.5-0.5B-Instruct | Q8 | Fits comfortably | 29.92 tok/sEstimated | 5GB (have 8GB) |
| Gensyn/Qwen2.5-0.5B-Instruct | FP16 | Not supported | 17.34 tok/sEstimated | 11GB (have 8GB) |
| meta-llama/Llama-3.1-8B-Instruct | Q4 | Fits comfortably | 44.67 tok/sEstimated | 4GB (have 8GB) |
| meta-llama/Llama-3.1-8B-Instruct | Q8 | Not supported | 30.85 tok/sEstimated | 9GB (have 8GB) |
| meta-llama/Llama-3.1-8B-Instruct | FP16 | Not supported | 16.56 tok/sEstimated | 17GB (have 8GB) |
| dphn/dolphin-2.9.1-yi-1.5-34b | Q4 | Not supported | 16.11 tok/sEstimated | 17GB (have 8GB) |
| dphn/dolphin-2.9.1-yi-1.5-34b | Q8 | Not supported | 11.60 tok/sEstimated | 35GB (have 8GB) |
| dphn/dolphin-2.9.1-yi-1.5-34b | FP16 | Not supported | 5.83 tok/sEstimated | 70GB (have 8GB) |
| openai/gpt-oss-20b | Q4 | Not supported | 22.65 tok/sEstimated | 10GB (have 8GB) |
| openai/gpt-oss-20b | Q8 | Not supported | 16.02 tok/sEstimated | 20GB (have 8GB) |
| openai/gpt-oss-20b | FP16 | Not supported | 8.57 tok/sEstimated | 41GB (have 8GB) |
| google/gemma-3-1b-it | Q4 | Fits comfortably | 52.57 tok/sEstimated | 1GB (have 8GB) |
| google/gemma-3-1b-it | Q8 | Fits comfortably | 33.54 tok/sEstimated | 1GB (have 8GB) |
| google/gemma-3-1b-it | FP16 | Fits comfortably | 19.98 tok/sEstimated | 2GB (have 8GB) |
| Qwen/Qwen3-Embedding-0.6B | Q4 | Fits comfortably | 39.80 tok/sEstimated | 3GB (have 8GB) |
| Qwen/Qwen3-Embedding-0.6B | Q8 | Fits comfortably | 33.49 tok/sEstimated | 6GB (have 8GB) |
| Qwen/Qwen3-Embedding-0.6B | FP16 | Not supported | 16.05 tok/sEstimated | 13GB (have 8GB) |
| Qwen/Qwen2.5-1.5B-Instruct | Q4 | Fits comfortably | 48.04 tok/sEstimated | 3GB (have 8GB) |
| Qwen/Qwen2.5-1.5B-Instruct | Q8 | Fits comfortably | 33.53 tok/sEstimated | 5GB (have 8GB) |
| Qwen/Qwen2.5-1.5B-Instruct | FP16 | Not supported | 15.80 tok/sEstimated | 11GB (have 8GB) |
| facebook/opt-125m | Q4 | Fits comfortably | 40.15 tok/sEstimated | 4GB (have 8GB) |
| facebook/opt-125m | Q8 | Fits (tight) | 33.94 tok/sEstimated | 7GB (have 8GB) |
| facebook/opt-125m | FP16 | Not supported | 17.60 tok/sEstimated | 15GB (have 8GB) |
| TinyLlama/TinyLlama-1.1B-Chat-v1.0 | Q4 | Fits comfortably | 53.73 tok/sEstimated | 1GB (have 8GB) |
| TinyLlama/TinyLlama-1.1B-Chat-v1.0 | Q8 | Fits comfortably | 36.71 tok/sEstimated | 1GB (have 8GB) |
| TinyLlama/TinyLlama-1.1B-Chat-v1.0 | FP16 | Fits comfortably | 18.21 tok/sEstimated | 2GB (have 8GB) |
| trl-internal-testing/tiny-Qwen2ForCausalLM-2.5 | Q4 | Fits comfortably | 46.15 tok/sEstimated | 4GB (have 8GB) |
| trl-internal-testing/tiny-Qwen2ForCausalLM-2.5 | Q8 | Fits (tight) | 33.35 tok/sEstimated | 7GB (have 8GB) |
| trl-internal-testing/tiny-Qwen2ForCausalLM-2.5 | FP16 | Not supported | 16.99 tok/sEstimated | 15GB (have 8GB) |
| Qwen/Qwen3-4B-Instruct-2507 | Q4 | Fits comfortably | 45.97 tok/sEstimated | 2GB (have 8GB) |
| Qwen/Qwen3-4B-Instruct-2507 | Q8 | Fits comfortably | 29.61 tok/sEstimated | 4GB (have 8GB) |
| Qwen/Qwen3-4B-Instruct-2507 | FP16 | Not supported | 16.25 tok/sEstimated | 9GB (have 8GB) |
| meta-llama/Llama-3.2-1B-Instruct | Q4 | Fits comfortably | 57.97 tok/sEstimated | 1GB (have 8GB) |
| meta-llama/Llama-3.2-1B-Instruct | Q8 | Fits comfortably | 35.57 tok/sEstimated | 1GB (have 8GB) |
| meta-llama/Llama-3.2-1B-Instruct | FP16 | Fits comfortably | 22.09 tok/sEstimated | 2GB (have 8GB) |
| openai/gpt-oss-120b | Q4 | Not supported | 8.59 tok/sEstimated | 59GB (have 8GB) |
| openai/gpt-oss-120b | Q8 | Not supported | 6.52 tok/sEstimated | 117GB (have 8GB) |
| openai/gpt-oss-120b | FP16 | Not supported | 3.69 tok/sEstimated | 235GB (have 8GB) |
| Qwen/Qwen2.5-3B-Instruct | Q4 | Fits comfortably | 56.27 tok/sEstimated | 2GB (have 8GB) |
| Qwen/Qwen2.5-3B-Instruct | Q8 | Fits comfortably | 35.62 tok/sEstimated | 3GB (have 8GB) |
| openai-community/gpt2 | Q4 | Fits comfortably | 48.29 tok/sEstimated | 4GB (have 8GB) |
Note: Performance estimates are calculated. Real results may vary. Methodology · Submit real data
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