QuadroProfessionalAmperePCIe 4CUDA
Operating mode
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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 RTX A4500 offers 20 GB of ECC GDDR6 at 640 GB/s bandwidth in NVIDIA's Ampere professional lineup, filling the gap between the 16 GB A4000 and 24 GB A5000. Its 20 GB capacity is unusual and particularly useful for models that exceed 16 GB at FP16 but do not need a full 24 GB. At $2,000 MSRP it is priced as a professional middle tier, suited for teams running 13B–20B models at FP16 or 30B models with light quantization in certified workstation environments.
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) | Needs offload | Qwen 3 30B Q4 | — |
workstation-gradeecc-memoryprofessional-certifiedmid-workstation
Specifications
Compute
FP1647 TFLOPS
INT8190 TOPS
ArchitectureAmpere
Memory
VRAM20 GB
Bandwidth640 GB/s
General
FamilyQuadro
SegmentProfessional
InterconnectPCIe 4
Compute PlatformCUDA
MSRP$2,000
Key Features
20 GB ECC GDDR6 VRAMAmpere 3rd-gen Tensor Cores47 TFLOPS FP16 / 190 INT8 TOPS640 GB/s memory bandwidthISV-certified professional driversPCIe 4.0 x16 interface
For AI Workloads
Strengths
- 20 GB ECC VRAM is an unusual sweet spot — fits 13B–20B models at FP16 without paying for 24 GB
- 47 TFLOPS FP16 offers solid throughput for a mid-range Ampere workstation card
- ECC and ISV certification suit deployment in regulated enterprise environments
- 640 GB/s bandwidth provides good decode performance for the 13B–20B model range
Considerations
- Ampere Tensor Cores lack FP8 support — inference efficiency lags Ada-generation alternatives
- $2,000 asks a workstation premium over consumer cards with similar compute and VRAM
- 20 GB is still insufficient for 30B FP16 inference — Q4 quantization required for 30B models
- Ada workstation replacements with FP8 support now available at comparable prices
Ampere is NVIDIA's second-generation RTX architecture, built on Samsung's 8nm process. It introduced 3rd-generation Tensor Cores with support for sparsity-accelerated INT8 operations and improved FP16 throughput over Turing.
AI Relevance
Sparsity-aware Tensor Cores can effectively double throughput for structured sparse workloads. However, the lack of FP8 support means quantized inference is less efficient than Ada Lovelace or Blackwell.
Process: Samsung 8nmPlatform: CUDATensor Cores: Gen 3Precisions: FP32, FP16, BF16, INT8, INT4
Recommendations by Workload
Qwen 3 14B 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 63.1 tok/s · 56K 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 76.4 tok/s · 71K 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 ~246.5 GB
123BTier 100Needs ~80.6 GB
1000BTier 100Needs ~616.6 GB
1000BTier 100Needs ~616.6 GB
1600BTier 100Needs ~865.8 GB
Image & Video Generation
Diffusion Model Compatibility
39 of 52 models can generate images or video on your RTX A4500 20GB
Upgrade paths
Upgrade from RTX A4500 20GB
See what you unlock with more powerful hardware
Upgrade options
Upgrade options
MacBook Pro M1 Max 32GBNext step up
32 GB Unified (+12)
AUnlocks 17 additional models that do not fit on the current setup.Unlocks Qwen 3.5 35B A3B, Qwen 3 32B, EXAONE 4.0 32B+14 more
Unlocks 17 additional models that do not fit on the current setup.
~$2,499 MSRP
👁 IntelIntel Arc Pro B60 24GBBest value 24 GB VRAM (+4)
AUnlocks 22 additional models that do not fit on the current setup.Unlocks Qwen 3.6 35B A3B, Qwen 3.5 35B A3B, Qwen 3 32B+19 more
Unlocks 22 additional models that do not fit on the current setup.
~$599 MSRP
24 GB VRAM (+4)1008 GB/s (+368)
AUnlocks 22 additional models that do not fit on the current setup.Unlocks Qwen 3.6 35B A3B, Qwen 3.5 35B A3B, Qwen 3 32B+19 more
Unlocks 22 additional models that do not fit on the current setup.
~$1,999 MSRP
AMD Instinct MI350X 288GBBiggest leap
288 GB VRAM (+268)8000 GB/s (+7360)
BUnlocks 67 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+64 more · +135% faster avg
Unlocks 67 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 135%.
~$8,000 MSRP
Frequently Asked Questions
20
GB
RTX A4500 20GBCategory AvgMacBook Pro M1 Max 32GB
LLM Large (70B)
| Image Gen (SDXL) | Runs natively | SDXL 1.0 FP16 | ~~6.8s per image |
| Image Gen (Flux) | Very constrained | Flux.1 Dev FP16 | ~~30.6s per image |
| Image Gen (SD 3.5) | Tight fit | SD 3.5 Large FP16 | ~~37.4s per image |
| Video Short (25f) | Runs natively | LTX Video 2B | ~~17.7s/frame |
| Video Long (100f) | Won't fit | Wan Video 14B | ~~17.4s/frame |
Qwen 3.5 9B 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, ollama, lm-studio.
Decode 76.4 tok/s · 71K ctx · llama.cppEST.
Qwen 3 14B 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 63.1 tok/s · 56K ctx · llama.cppEST.
Granite 4.1 8B matches RAG and keeps a practical fit profile. 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 85.9 tok/s · 69K ctx · llama.cppEST.
9B
10.6 GB
98 tok/s
85K ctx
Image
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 RTX A4500 20GB for local AI?
Good for local AI
Handles 21 of 50 top models. Smaller and mid-size models run comfortably.
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 17 additional models that do not fit on the current setup.
Want more headroom? MacBook Pro M1 Max 32GB (32.0 GB unified memory) is the next step up.
