Why memory bandwidth matters more than TFLOPS for LLM inference
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Your GPU's TFLOPS rating does not decide how fast it generates tokens. Memory bandwidth does. Here's the spec that actually separates A100-era inference from H200-era inference. Key takeaways HBM3e reaches up to 9.6 Gb/s per pin versus HBM2e's 3.2 Gb/s, tripling per-pin signalling speed with the same 1,024-bit interface width. Total GPU memory bandwidth jumps from 2.0 TB/s on the A100 (HBM2e) to 4.8 TB/s on the H200 (HBM3e), a 140% increase, and 8.0 TB/s on the B200. LLM token generation…
1Key Takeaways
- Your GPU's TFLOPS rating does not decide how fast it generates tokens.
- Here's the spec that actually separates A100-era inference from H200-era inference.
- Key takeaways HBM3e reaches up to 9.6 Gb/s per pin versus HBM2e's 3.2 Gb/s, tripling per-pin signalling speed with the same 1,024-bit interface width.
- Total GPU memory bandwidth jumps from 2.0 TB/s on the A100 (HBM2e) to 4.8 TB/s on the H200 (HBM3e), a 140% increase, and 8.0 TB/s on the B200.
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — ML reports that your GPU's TFLOPS rating does not decide how fast it generates tokens.
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