RX 7000ConsumerRDNA 3PCIe 4ROCm
Operating mode
Choose the operating mode for this hardware
Use this to bias workload recommendations toward responsiveness, background autonomy, lighter serving, or multi-GPU scale-out.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
About this GPU for AI
The RX 7700 XT 12GB sits in the mid-range RDNA 3 lineup, offering solid 1080p/1440p gaming performance and reasonable AI inference capability. With 12 GB of GDDR6 VRAM it can handle 7B models at FP16 and 13B at Q4. Community ROCm support is available for RDNA 3, and the 7700 XT works with the HSA_OVERRIDE_GFX_VERSION workaround, though it is not officially listed by AMD.
Beyond LLMs
AI Capability Matrix
What AI tasks this GPU can handle — from text generation to image and video creation.
| Capability | Status | Representative Model | Detail |
|---|
| LLM Chat (7B) | Runs natively | Llama 3.1 8B Q4 | — |
| LLM Coding (30B) | Won’t fit | Qwen 3 30B Q4 | — |
| LLM Large (70B) |
rocm-experimentalmid-rangesoftware-limited
Specifications
Compute
FP1635 TFLOPS
INT8280 TOPS
ArchitectureRDNA 3
Memory
VRAM12 GB
Bandwidth432 GB/s
TypeGDDR6
General
FamilyRX 7000
SegmentConsumer
InterconnectPCIe 4
Compute PlatformROCM
MSRP$449
TDP245W
Key Features
RDNA 3 architecture (Navi 32 die)12 GB GDDR6 on a 192-bit bus432 GB/s memory bandwidth54 Compute UnitsAMD Infinity Cache (second-generation)Community ROCm support via gfx1100 workaround
For AI Workloads
Strengths
- 12 GB VRAM handles 7B FP16 and 13B Q4 models without CPU offloading
- 432 GB/s bandwidth is reasonable for mid-range decode throughput
- Community ROCm works reliably on RDNA 3 with correct environment variables
- Good gaming/AI balance for users wanting dual-purpose hardware
Considerations
- Not officially ROCm supported — environment variable workarounds needed
- Community ROCm support can break with AMD driver updates
- High TDP (245W) for a mid-range card affects power efficiency
- NVIDIA RTX 4060 12GB matches it in AI performance with native CUDA
RDNA 3 is AMD's chiplet-based GPU architecture, combining a 5nm Graphics Compute Die (GCD) with 6nm Memory Cache Dies (MCDs). It introduces AI accelerators and a new unified compute unit design.
AI Relevance
ROCm support for RDNA 3 is maturing but lags behind NVIDIA's CUDA ecosystem. AI accelerator units provide some inference acceleration, but lack the dedicated Tensor Core equivalent found in NVIDIA GPUs.
Process: TSMC 5nm + 6nmPlatform: ROCMPrecisions: FP32, FP16, BF16, INT8
Recommendations by Workload
Qwen 3.5 9B matches Chat and keeps a practical fit profile. It is a recent-generation family, which helps on current local SOTA workloads. It fits natively with comfortable headroom. Context coverage stays within the requested workload envelope. Known distribution channels: huggingface, ollama, lm-studio.
Decode 50.8 tok/s · 32K ctx · llama.cppEST.
Qwen 3.5 9B is a specialized fit for Coding. It is a recent-generation family, which helps on current local SOTA workloads. It fits natively with comfortable headroom. Context coverage stays within the requested workload envelope. Known distribution channels: huggingface, ollama, lm-studio.
Decode 50.8 tok/s · 32K ctx · llama.cppEST.
Just out of reach
Models you could run with an upgrade
High-quality models that need a bit more memory
30.5BTier 100Needs ~21.4 GB
397BTier 100Needs ~245.7 GB
123BTier 100Needs ~79.8 GB
1000BTier 100Needs ~615.8 GB
1000BTier 100Needs ~615.8 GB
Image & Video Generation
Diffusion Model Compatibility
24 of 52 models can generate images or video on your RX 7700 XT 12GB
Upgrade paths
Upgrade from RX 7700 XT 12GB
See what you unlock with more powerful hardware
Upgrade options
Upgrade options
Frequently Asked Questions
RX 7700 XT 12GBCategory AvgMacBook Pro M3 Pro 18GB
| Image Gen (SDXL) | Runs natively | SDXL 1.0 FP16 | ~~11.9s per image |
| Image Gen (Flux) | Won't fit | Flux.1 Dev FP16 | ~~53.4s per image |
| Image Gen (SD 3.5) | Won't fit | SD 3.5 Large FP16 | ~~1m 5s per image |
| Video Short (25f) | Runs with offload | LTX Video 2B | ~~10.3s/frame |
| Video Long (100f) | Won't fit | Wan Video 14B | ~~30.3s/frame |
CodeGeeX 4 9B is a specialized fit for Agentic Coding. It sits in the middle of the current generation mix. It fits natively with comfortable headroom. Context coverage stays within the requested workload envelope. Known distribution channels: huggingface, ollama.
Decode 51.6 tok/s · 116K ctx · llama.cppEST.
Qwen 3.5 9B matches Reasoning and keeps a practical fit profile. It is a recent-generation family, which helps on current local SOTA workloads. It fits natively with comfortable headroom. Context coverage stays within the requested workload envelope. Known distribution channels: huggingface, ollama, lm-studio.
Decode 50.8 tok/s · 32K ctx · llama.cppEST.
CodeGeeX 4 9B is viable for RAG, but is not the most specialized choice. It sits in the middle of the current generation mix. It fits natively with comfortable headroom. Context coverage stays within the requested workload envelope. Known distribution channels: huggingface, ollama.
Decode 51.6 tok/s · 116K ctx · llama.cppEST.
4B
6.7 GB
56 tok/s
54K ctx
Image
| MAGI-1Video | 256×256 | ~27.8s/frame | F |
Image models estimated at 1024×1024 (28 steps, FP16). Video models estimated at 768×512 (25 frames, 30 steps, FP16). Actual performance varies with runtime and system load.
Buying advice
Should you buy RX 7700 XT 12GB for local AI?
Usable for local AI with limits
Can run 10 of 50 top models, mostly smaller ones. Larger models need heavy quantization or won't fit.
What will limit you first
This setup is broadly balanced for this model.
No major red flags
This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.
Best upgrade itinerary
Unlocks 1 additional models that do not fit on the current setup.
Want more headroom? MacBook Pro M3 Pro 18GB (18.0 GB unified memory) is the next step up.
