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Graphcore GC200 vs Graphcore Bow IPU

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

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

Specifications

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GC200
Graphcore logo
Bow IPU
Architecture
Colossus MK2Colossus MK2
Launch Year
20202022
Form Factor
——
Memory
——
Memory Bandwidth
——
TDP
——
Process Node
7nm—

Performance (TFLOPS)

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GC200
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Bow IPU
FP64
No verified data available No verified data available
FP32
63 TFLOPS 87 TFLOPS
TF32
No verified data available No verified data available
BF16
No verified data available No verified data available
FP16
250 TFLOPS 350 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 GC200 against the Bow IPU: FP32 63 vs 87 TFLOPS, FP16 250 vs 350 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 GC200 faster than the Bow IPU?

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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