# RuntimeError: Tensor Cores are not supported on the current device architecture (compute capability < 7.0)

- **ID:** `cuda/tensor-core-unsupported-arch`
- **Domain:** cuda
- **Category:** type_error
- **Error Code:** `CUDNN_STATUS_ARCH_MISMATCH`
- **Verification:** ai_generated
- **Fix Rate:** 90%

## Root Cause

The GPU compute capability is below 7.0 (Volta), which is required for Tensor Core operations like mixed-precision training with float16 or bfloat16.

## Version Compatibility

| Version | Status | Introduced | Deprecated |
|---------|--------|------------|------------|
| CUDA 11.0 | active | — | — |
| CUDA 12.1 | active | — | — |
| CUDA 12.4 | active | — | — |

## Workarounds

1. **Disable Tensor Core usage by setting torch.backends.cuda.matmul.allow_tf32 = False and torch.backends.cudnn.allow_tf32 = False, and use float32 precision instead of float16. For example: model.half() should be replaced with model.float(); and in training, use torch.amp.autocast(device_type='cuda', enabled=False).** (90% success)
   ```
   Disable Tensor Core usage by setting torch.backends.cuda.matmul.allow_tf32 = False and torch.backends.cudnn.allow_tf32 = False, and use float32 precision instead of float16. For example: model.half() should be replaced with model.float(); and in training, use torch.amp.autocast(device_type='cuda', enabled=False).
   ```
2. **If Tensor Cores are essential, migrate to a GPU with compute capability >= 7.0 (e.g., Tesla V100, RTX 20 series, or newer). Check your GPU's compute capability at https://developer.nvidia.com/cuda-gpus.** (95% success)
   ```
   If Tensor Cores are essential, migrate to a GPU with compute capability >= 7.0 (e.g., Tesla V100, RTX 20 series, or newer). Check your GPU's compute capability at https://developer.nvidia.com/cuda-gpus.
   ```

## Dead Ends

- **** — Upgrading the CUDA toolkit does not add Tensor Core support to older GPU architectures. (90% fail)
- **** — Setting environment variable CUDA_LAUNCH_BLOCKING=1 does not enable Tensor Cores; it only serializes kernel launches. (80% fail)