AMD GPU Comparison: Max+ 395 vs RX 7900 for LLM Inference

Source

This report compares the inference performance of two GPU systems running local LLM models using Ollama. The benchmark tests were conducted using the llm-tester tool with concurrent requests set to 1, simulating single-user workload scenarios.

Test Configuration

Systems Tested

  1. AI Max+ 395

    • Host: bosgame.localnet
    • ROCm: Custom installation in home directory
    • Memory: 32 GB unified memory
    • VRAM: 96 GB

  2. AMD Radeon RX 7900 XTX

    • Host: rig.localnet
    • ROCm: System default installation
    • Memory: 96 GB
    • VRAM: 24 GB

Models Tested

Test Methodology

  • Benchmark Tool: llm-tester (https://github.com/Laszlobeer/llm-tester)
  • Concurrent Requests: 1 (single-user simulation)
  • Tasks per Model: 5 diverse prompts
  • Timeout: 180 seconds per task
  • Backend: Ollama API (http://localhost:11434)

Performance Results

deepseek-r1:1.5b Performance

System Avg Tokens/s Avg Latency Total Time Performance Ratio
AMD RX 7900 197.01 6.54s 32.72s 1.78x faster
Max+ 395 110.52 21.51s 107.53s baseline

Detailed Results - AMD RX 7900:

  • Task 1: 196.88 tokens/s, Latency: 9.81s
  • Task 2: 185.87 tokens/s, Latency: 17.60s
  • Task 3: 200.72 tokens/s, Latency: 1.97s
  • Task 4: 200.89 tokens/s, Latency: 1.76s
  • Task 5: 200.70 tokens/s, Latency: 1.57s

Detailed Results - Max+ 395:

  • Task 1: 111.78 tokens/s, Latency: 13.38s
  • Task 2: 93.81 tokens/s, Latency: 82.23s
  • Task 3: 115.97 tokens/s, Latency: 3.83s
  • Task 4: 114.72 tokens/s, Latency: 4.52s
  • Task 5: 116.34 tokens/s, Latency: 3.57s

AMD RX 7900 XTX running deepseek-r1:1.5b benchmark

AMD RX 7900 XTX performance on deepseek-r1:1.5b model

Max+ 395 running deepseek-r1:1.5b benchmark

Max+ 395 performance on deepseek-r1:1.5b model

qwen3:latest Performance

System Avg Tokens/s Avg Latency Total Time Performance Ratio
AMD RX 7900 86.46 12.81s 64.04s 2.71x faster
Max+ 395 31.85 41.00s 204.98s baseline

Detailed Results - AMD RX 7900:

  • Task 1: 86.56 tokens/s, Latency: 15.07s
  • Task 2: 85.69 tokens/s, Latency: 18.37s
  • Task 3: 86.74 tokens/s, Latency: 7.15s
  • Task 4: 87.91 tokens/s, Latency: 1.56s
  • Task 5: 85.43 tokens/s, Latency: 21.90s

Detailed Results - Max+ 395:

  • Task 1: 32.21 tokens/s, Latency: 33.15s
  • Task 2: 27.53 tokens/s, Latency: 104.82s
  • Task 3: 33.47 tokens/s, Latency: 16.79s
  • Task 4: 34.96 tokens/s, Latency: 4.64s
  • Task 5: 31.08 tokens/s, Latency: 45.59s

AMD RX 7900 XTX running qwen3:latest benchmark

AMD RX 7900 XTX performance on qwen3:latest model

Max+ 395 running qwen3:latest benchmark

Max+ 395 performance on qwen3:latest model

Comparative Analysis

Overall Performance Summary

Model RX 7900 Max+ 395 Performance Multiplier
deepseek-r1:1.5b 197.01 tok/s 110.52 tok/s 1.78x
qwen3:latest 86.46 tok/s 31.85 tok/s 2.71x

Key Findings

  1. RX 7900 Dominance: The AMD RX 7900 significantly outperforms the Max+ 395 across both models
  2. 78% faster on deepseek-r1:1.5b

  3. 171% faster on qwen3:latest

  4. Model-Dependent Performance Gap: The performance difference is more pronounced with the larger/more complex model (qwen3:latest), suggesting the RX 7900 handles larger models more efficiently

  5. Consistency: The RX 7900 shows more consistent performance across tasks, with lower variance in latency

  6. Total Execution Time:

  7. For deepseek-r1:1.5b: RX 7900 completed in 32.72s vs 107.53s (3.3x faster)
  8. For qwen3:latest: RX 7900 completed in 64.04s vs 204.98s (3.2x faster)

Comparison with Previous Results

Desktop PC (i9-9900k + RTX 2080, 8GB VRAM)

  • deepseek-r1:1.5b: 143 tokens/s
  • qwen3:latest: 63 tokens/s

M4 Mac (24GB Unified Memory)

  • deepseek-r1:1.5b: 81 tokens/s
  • qwen3:latest: Timeout issues (needed 120s timeout)

Performance Ranking

deepseek-r1:1.5b:

  1. AMD RX 7900: 197.01 tok/s ⭐
  2. RTX 2080 (CUDA): 143 tok/s
  3. Max+ 395: 110.52 tok/s
  4. M4 Mac: 81 tok/s

qwen3:latest:

  1. AMD RX 7900: 86.46 tok/s ⭐
  2. RTX 2080 (CUDA): 63 tok/s
  3. Max+ 395: 31.85 tok/s
  4. M4 Mac: Unable to complete within timeout

Cost-Benefit Analysis

System Pricing Context

  • Framework Desktop with Max+ 395: ~$2,500
  • AMD RX 7900: Available as standalone GPU (~$600-800 used, ~$900-1000 new)

Value Proposition

The AMD RX 7900 delivers:

  • 1.78-2.71x better performance than the Max+ 395
  • Significantly better price-to-performance ratio (~$800 vs $2,500)
  • Dedicated GPU VRAM vs shared unified memory
  • Better thermal management in desktop form factor

The $2,500 Framework Desktop investment could alternatively fund:

  • AMD RX 7900 GPU
  • High-performance desktop motherboard
  • AMD Ryzen CPU
  • 32-64GB DDR5 RAM
  • Storage and cooling
  • With budget remaining

Conclusions

  1. Clear Performance Winner: The AMD RX 7900 is substantially faster than the Max+ 395 for LLM inference workloads

  2. Value Analysis: The Framework Desktop's $2,500 price point doesn't provide competitive performance for LLM workloads compared to desktop alternatives

  3. Use Case Consideration: The Framework Desktop offers portability and unified memory benefits, but if LLM performance is the primary concern, the RX 7900 desktop configuration is superior

  4. ROCm Compatibility: Both systems successfully ran ROCm workloads, demonstrating AMD's growing ecosystem for AI/ML tasks

  5. Recommendation: For users prioritizing LLM inference performance per dollar, a desktop workstation with an RX 7900 provides significantly better value than the Max+ 395 Framework Desktop

Technical Notes

  • All tests used identical benchmark methodology with single concurrent requests
  • Both systems were running similar ROCm configurations
  • Network latency was negligible (local Ollama API)
  • Results represent real-world single-user inference scenarios

Systems Information

Both systems are running:

  • Operating System: Linux
  • LLM Runtime: Ollama
  • Acceleration: ROCm (AMD GPU compute)
  • Python: 3.12.3