AMD RX 6700 XT - 12GB usable
Specifications
| Brand | AMD |
|---|---|
| Model | RX 6700 XT |
| Usable VRAM | 12GB |
| Architecture | RDNA2 |
| CUDA / Stream Processors | 2,560 |
| Memory Bandwidth | 384 GB/s |
| TDP | 230W |
| FP32 TFLOPS | 13.2 |
Current Offers
Prices last updated:
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Lowest tracked offers by retailer
US · USD · Weekly since May 2026 · Shipping may be extra
About these prices
Each line is the lowest offer we tracked from that retailer at weekly snapshots, ending at today's offer. The condition can vary between snapshots (new, used, or unrecorded for older ones). eBay prices exclude shipping. Tax is excluded. Amazon shows a current price only.
Weekly offers table
| Date | eBay | Amazon | Newegg |
|---|---|---|---|
| Today, Nov 3, 2026 | $330.00 | $409.97 | – |
| Oct 30, 2026 | $349.99 | – | – |
| Oct 23, 2026 | $310.00 | – | – |
| Oct 9, 2026 | $317.79 | – | – |
| Oct 2, 2026 | $230.00 | – | $319.99 |
| Sep 25, 2026 | $317.79 | – | $319.99 |
| Sep 18, 2026 | $299.99 | – | – |
| Sep 11, 2026 | $295.00 | – | $309.99 |
| Sep 4, 2026 | – | – | $309.99 |
| Sep 1, 2026 | – | – | $309.99 |
| Aug 28, 2026 | – | – | $309.99 |
| Aug 21, 2026 | – | – | $309.49 |
| Aug 14, 2026 | – | – | $309.49 |
| Aug 7, 2026 | $275.00 | – | $309.99 |
| Jul 31, 2026 | $299.99 | – | $309.49 |
| Jul 24, 2026 | – | – | $322.00 |
| Jul 17, 2026 | $275.00 | – | $269.49 |
| Jul 10, 2026 | – | – | $269.49 |
| Jul 3, 2026 | $255.99 | – | $328.00 |
| Jun 26, 2026 | $279.99 | – | $789.00 |
| Jun 19, 2026 | $288.00 | – | $328.00 |
| Jun 12, 2026 | – | – | $328.00 |
| Jun 5, 2026 | – | – | $269.49 |
| May 29, 2026 | – | – | $779.00 |
| May 22, 2026 | – | – | $789.00 |
| May 15, 2026 | – | – | $359.00 |
| May 8, 2026 | – | – | $344.99 |
For AI / LLM Use
Entry-level for local AI. Handles 7B-8B models well. Slower generation, usable but not snappy. Verify ROCm support for the exact framework and operating system you plan to use.
What Models Can It Run?
- 14B Q4_K_M, 7B full precision
- 7B Q6_K, 14B Q3_K (tight)
- 7B Q4_K_M only
Estimated Performance
Generation: ~29 tokens/sec
Prefill: ~236 tokens/sec
Recommended Quantisations
- Q4_K_M for 14B (tight fit)
- Q6_K or Q8 for 7B models
Pros & Cons
Pros
- RDNA2 architecture: supported by current ROCm stacks
- Consumer card: easy to install, display output
Cons
- 12GB usable VRAM: may need quantization for 30B+ models
- Moderate memory bandwidth: not the fastest for inference
- ROCm and CUDA-first framework compatibility should be checked before purchase
Community Verdict
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