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Graphcore Bow IPU vs Graphcore GC200

The Bow IPU delivers 40% more FP16 throughput than the GC200 (350 vs 250 TFLOPS dense).

Bow IPU: Colossus MK2, 2022 GC200: Colossus MK2, 2020
FP16 dense lead
+40%
Bow IPU: 350 vs 250 TFLOPS

Specifications

Graphcore logo
Bow IPU
Graphcore logo
GC200
Architecture
Colossus MK2Colossus MK2
Launch Year
20222020
Form Factor
——
Memory
——
Memory Bandwidth
——
TDP
——
Process Node
—7nm

Performance (TFLOPS)

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Bow IPU
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GC200
FP64
No verified data available No verified data available
FP32
87 TFLOPS 63 TFLOPS
TF32
No verified data available No verified data available
BF16
No verified data available No verified data available
FP16
350 TFLOPS 250 TFLOPS
FP8
No verified data available No verified data available
FP6
No verified data available No verified data available
FP4
No verified data available No verified data available
INT8
No verified data available No verified data available

FLOPS by Precision

What actually differs

The Bow IPU is the newer part: Colossus MK2, launched in 2022, against the GC200's Colossus MK2 from 2020. Newer architectures typically add lower-precision formats and better throughput per watt, so check the precision rows your workload actually uses.

Dense throughput for the Bow IPU against the GC200: FP32 87 vs 63 TFLOPS, FP16 350 vs 250 TFLOPS. Sparse figures, where the vendor publishes them, appear under each dense number in the performance table.

For LLM training and inference, weight the FP8 and FP16 rows and memory capacity most heavily. For scientific and HPC workloads, the FP64 row is the one to read.

Frequently asked questions

Is the Bow IPU faster than the GC200?

At FP16 precision the Bow IPU reaches 350 TFLOPS dense against 250 TFLOPS for the GC200. The performance table on this page lists every published precision for both GPUs.

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