diff --git a/jax/_src/pallas/triton/lowering.py b/jax/_src/pallas/triton/lowering.py
index b170822ea873..c333f5e65877 100644
--- a/jax/_src/pallas/triton/lowering.py
+++ b/jax/_src/pallas/triton/lowering.py
@@ -59,7 +59,7 @@
 import numpy as np
 from triton._C.libtriton.triton import ir as tl_ir
 from triton.compiler import code_generator as code_gen
-from triton.compiler import compiler as tc
+import triton.compiler.backends.cuda as cb
 import triton.language as tl
 
 # TODO(sharadmv): enable type checking
@@ -229,21 +229,13 @@ def _process_grid_to_3d_grid(builder, grid_mapping: GridMapping):
 
 def lower_jaxpr_to_triton_module(
     jaxpr: jax_core.Jaxpr, in_shapes, grid_mapping: GridMapping, name: str,
-    num_warps: int
+    cuda_options: cb.CUDAOptions
 ) -> tl_ir.module:
   jaxpr, _ = pe.dce_jaxpr(jaxpr, [True] * len(jaxpr.outvars), instantiate=True)
   ir_context = tl_ir.context()
   ir_context.load_triton()
   builder = tl_ir.builder(ir_context)
-  # TODO(sharadmv): handle multiple devices, right now we assume device 0
-  # which is fine when we have multiple of the same GPU but this won't work in
-  # general.
-  device = 0
-  builder.target = tc.CudaTargetDescriptor(
-      capability=triton_kernel_call_lib.get_compute_capability(device),
-      num_warps=num_warps,
-      enable_fp_fusion=True
-  )
+  builder.options = cuda_options
   module = builder.create_module()
   in_avals = [var.aval for var in jaxpr.invars]
   triton_types = [get_triton_type(x) for x in in_avals]
@@ -1491,17 +1483,31 @@ def compile_jaxpr(
     num_stages: int,
     debug: bool,
 ) -> TritonCompilationResult:
+  # TODO(sharadmv): handle multiple devices, right now we assume device 0
+  # which is fine when we have multiple of the same GPU but this won't work in
+  # general.
+  device = 0
+  arch = triton_kernel_call_lib.get_compute_capability(device)
+  target = ("cuda", arch)
+  cuda_backend = cb.CUDABackend(target)
+  cuda_options = cuda_backend.parse_compiler_options(
+      dict(
+          num_warps=num_warps,
+          num_stages=num_stages,
+          debug=debug,
+      )
+  )
+
   lowering_result = lower_jaxpr_to_triton_module(
-      jaxpr, in_shapes, grid_mapping, name, num_warps
+      jaxpr, in_shapes, grid_mapping, name, cuda_options
   )
-  device = 0
+
   ttir = str(lowering_result.module)
   ptx, name, shared_mem_bytes, compute_capability = compile_ttir_to_ptx_inplace(
       lowering_result.module,
+      cuda_backend,
+      cuda_options,
       device=device,
-      num_warps=num_warps,
-      num_stages=num_stages,
-      dump=debug,
   )
   return TritonCompilationResult(
       name, ttir, ptx, shared_mem_bytes, compute_capability, lowering_result