AMD
AMD Instinct MI60 32GB
InstinctDatacenterVegaPCIe 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 AMD Instinct MI60 32GB is an older Vega-based datacenter GPU from 2018, one of AMD's first serious HPC accelerators. While it has full ROCm support (being a datacenter Instinct card), the Vega architecture is old and the 29 TFLOPS FP16 compute is very modest by modern standards. The 32 GB of HBM2 VRAM is its main AI asset, but newer Instinct cards offer dramatically better compute at lower cost on the used market.
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) | Runs natively | Qwen 3 30B Q4 | — |
| LLM Large (70B) |
rocm-supporteddatacenter-gradelegacyhigh-bandwidth
Specifications
Compute
FP1629 TFLOPS
INT858 TOPS
ArchitectureVega
Memory
VRAM32 GB
Bandwidth1024 GB/s
General
FamilyInstinct
SegmentDatacenter
InterconnectPCIe 4
Compute PlatformROCM
MSRP$8,999
Key Features
Vega (GCN 5) architecture — AMD's HPC-focused Vega 20 die32 GB HBM2 on a 4096-bit bus1 TB/s memory bandwidthFull ROCm support — Instinct datacenter cardPCIe Gen 3/4 x16Legacy ROCm support may require older toolchain versions
For AI Workloads
Strengths
- Full ROCm support as an Instinct datacenter card
- 32 GB HBM2 with 1 TB/s bandwidth — memory bandwidth is a strength
- HBM2 delivers very high bandwidth for memory-bandwidth-bound inference
- Full ROCm software stack compatible
Considerations
- 29 TFLOPS FP16 is very low compute — slow token generation
- Vega architecture is significantly older than CDNA — less efficient AI kernels
- Newer ROCm versions may drop or reduce support for legacy Vega
- MI100 or MI210 are far better choices for actual AI workloads
Vega is AMD's GCN 5th generation architecture, featuring HBM2 memory and high compute density. Used in consumer Vega cards and the Instinct MI60 datacenter accelerator.
AI Relevance
The Instinct MI60 with 32 GB HBM2 and ROCm support can run LLM inference, but its age means limited compatibility with modern AI frameworks. Consumer Vega cards have insufficient VRAM for meaningful AI work.
Process: GlobalFoundries 14nmPlatform: ROCMPrecisions: FP64, FP32, FP16
Recommendations by Workload
Qwen 3.5 35B A3B 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 69.3 tok/s · 72K ctx · llama.cppEST.
Qwen 3.6 27B 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, lm-studio.
Decode 20.5 tok/s · 187K ctx · llama.cppEST.
Just out of reach
Models you could run with an upgrade
High-quality models that need a bit more memory
397BTier 100Needs ~247.7 GB
123BTier 100Needs ~81.8 GB
1000BTier 100Needs ~617.8 GB
1000BTier 100Needs ~617.8 GB
1600BTier 100Needs ~867.0 GB
Image & Video Generation
Diffusion Model Compatibility
43 of 52 models can generate images or video on your AMD Instinct MI60 32GB
Upgrade paths
Upgrade from AMD Instinct MI60 32GB
See what you unlock with more powerful hardware
Upgrade options
Upgrade options
MacBook Pro M1 Max 64GBNext step up
64 GB Unified (+32)
AUnlocks 11 additional models that do not fit on the current setup.Unlocks Qwen 2.5 VL 72B, Llama 3.3 70B, Llama 3.1 70B+8 more
Unlocks 11 additional models that do not fit on the current setup.
~$2,499 MSRP
Radeon PRO W7900 DS 48GBAMD upgrade
48 GB VRAM (+16)
AUnlocks 13 additional models that do not fit on the current setup.Unlocks Qwen 2.5 VL 72B, Qwen3-Coder-Next, Llama 3.3 70B+10 more
Unlocks 13 additional models that do not fit on the current setup.
~$3,999 MSRP
MacBook Pro M3 Max 128GBBest value
128 GB Unified (+96)
BUnlocks 26 additional models that do not fit on the current setup.Unlocks Devstral 2 123B Instruct, Qwen 3.5 122B A10B, Mistral Small 4 119B+23 more
Unlocks 26 additional models that do not fit on the current setup.
~$2,499 MSRP
AMD Instinct MI350X 288GBBiggest leap
288 GB VRAM (+256)8000 GB/s (+6976)
BUnlocks 39 additional models that do not fit on the current setup.Unlocks Qwen 3.5 397B A17B, Devstral 2 123B Instruct, Qwen 3.5 122B A10B+36 more · +144% faster avg
Unlocks 39 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 144%.
~$8,000 MSRP
Frequently Asked Questions
AMD Instinct MI60 32GBCategory AvgMacBook Pro M1 Max 64GB
| Image Gen (SDXL) | Runs natively | SDXL 1.0 FP16 | ~~17.5s per image |
| Image Gen (Flux) | Runs natively | Flux.1 Dev FP16 | ~~2m 18s per image |
| Image Gen (SD 3.5) | Runs natively | SD 3.5 Large FP16 | ~~1m 37s per image |
| Video Short (25f) | Runs natively | LTX Video 2B | ~~15.2s/frame |
| Video Long (100f) | Won't fit | Wan Video 14B | ~~44.8s/frame |
Qwen 3.6 27B is a specialized fit for Agentic 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, lm-studio.
Decode 20.5 tok/s · 187K ctx · llama.cppEST.
Devstral Small 2 24B Instruct 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 36.8 tok/s · 87K ctx · llama.cppEST.
Qwen 3.5 27B matches RAG and keeps a practical fit profile. It is a recent-generation family, which helps on current local SOTA workloads. It should run, but memory headroom will be limited. Context coverage stays within the requested workload envelope. Known distribution channels: huggingface, ollama, lm-studio.
Decode 32.9 tok/s · 58K ctx · llama.cppEST.
30.5B24.2 GB76 tok/s102K ctx
Image
| MAGI-1Video | 256×256 | ~41.2s/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 AMD Instinct MI60 32GB for local AI?
Excellent choice for local AI
Runs 27 of 50 top models well — a strong all-rounder for local inference.
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 11 additional models that do not fit on the current setup.
Want more headroom? MacBook Pro M1 Max 64GB (64.0 GB unified memory) is the next step up.
