diff --git a/mlx/random.h b/mlx/random.h
new file mode 100644
index 000000000..25dc9f924
--- /dev/null
+++ b/mlx/random.h
@@ -0,0 +1,191 @@
+#pragma once
+
+#include <optional>
+
+#include "mlx/array.h"
+#include "mlx/stream.h"
+
+namespace mlx::core::random {
+
+class KeySequence {
+ public:
+  explicit KeySequence(uint64_t seed);
+
+  void seed(uint64_t seed);
+  array next();
+
+  // static defualt
+  static KeySequence& default_() {
+    static KeySequence ks(0);
+    return ks;
+  }
+
+ private:
+  array key_;
+};
+
+/** Get a PRNG key from a seed. */
+array key(uint64_t seed);
+
+/** Seed the default PRNG key. */
+void seed(uint64_t seed);
+
+/** Generate an array with type uint32 filled with random bits. */
+array bits(
+    const std::vector<int>& shape,
+    int width,
+    const std::optional<array>& key = std::nullopt,
+    StreamOrDevice s = {});
+inline array bits(
+    const std::vector<int>& shape,
+    const std::optional<array>& key = std::nullopt,
+    StreamOrDevice s = {}) {
+  return bits(shape, 4, key, s);
+}
+
+/** Split the rng key into a pair of keys. */
+std::pair<array, array> split(const array& key, StreamOrDevice s = {});
+
+/** Split the rng key into `num` keys. */
+array split(const array& key, int num, StreamOrDevice s = {});
+
+/** Generate uniform random numbers between low and high. */
+array uniform(
+    const array& low,
+    const array& high,
+    const std::vector<int>& shape,
+    Dtype dtype = float32,
+    const std::optional<array>& key = std::nullopt,
+    StreamOrDevice s = {});
+
+template <typename T, typename U>
+array uniform(
+    T low,
+    U high,
+    const std::vector<int>& shape,
+    Dtype dtype = float32,
+    const std::optional<array>& key = std::nullopt,
+    StreamOrDevice s = {}) {
+  return uniform(array(low), array(high), shape, dtype, key, to_stream(s));
+}
+
+/** Generate uniform random numbers between 0 and 1. */
+array uniform(
+    const std::vector<int>& shape,
+    Dtype dtype,
+    const std::optional<array>& key = std::nullopt,
+    StreamOrDevice s = {});
+inline array uniform(
+    const std::vector<int>& shape,
+    const std::optional<array>& key = std::nullopt,
+    StreamOrDevice s = {}) {
+  return uniform(shape, float32, key);
+}
+
+/** Generate samples from the standard normal distribution. */
+array normal(
+    const std::vector<int>& shape,
+    Dtype dtype,
+    const std::optional<array>& key = std::nullopt,
+    StreamOrDevice s = {});
+inline array normal(
+    const std::vector<int>& shape,
+    const std::optional<array>& key = std::nullopt,
+    StreamOrDevice s = {}) {
+  return normal(shape, float32, key, s);
+}
+
+/** Generate integer samples uniformly at random */
+array randint(
+    const array& low,
+    const array& high,
+    const std::vector<int>& shape,
+    Dtype dtype = int32,
+    const std::optional<array>& key = std::nullopt,
+    StreamOrDevice s = {});
+
+template <typename T, typename U>
+array randint(
+    T low,
+    U high,
+    const std::vector<int>& shape,
+    Dtype dtype = int32,
+    const std::optional<array>& key = std::nullopt,
+    StreamOrDevice s = {}) {
+  return randint(array(low), array(high), shape, dtype, key, to_stream(s));
+};
+
+/** Generate binary variables with probability to be true equal to p */
+array bernoulli(
+    const array& p,
+    const std::vector<int>& shape,
+    const std::optional<array>& key = std::nullopt,
+    StreamOrDevice s = {});
+array bernoulli(
+    const array& p,
+    const std::optional<array>& key = std::nullopt,
+    StreamOrDevice s = {});
+
+template <typename T>
+array bernoulli(
+    T p,
+    const std::optional<array>& key = std::nullopt,
+    StreamOrDevice s = {}) {
+  return bernoulli(array(p), key, s);
+};
+
+template <typename T>
+array bernoulli(
+    T p,
+    const std::vector<int>& shape,
+    const std::optional<array>& key = std::nullopt,
+    StreamOrDevice s = {}) {
+  return bernoulli(array(p), shape, key, s);
+};
+
+array bernoulli(
+    const std::optional<array>& key = std::nullopt,
+    StreamOrDevice s = {});
+
+array truncated_normal(
+    const array& lower,
+    const array& upper,
+    const std::vector<int>& shape,
+    Dtype dtype = float32,
+    const std::optional<array>& key = std::nullopt,
+    StreamOrDevice s = {});
+
+array truncated_normal(
+    const array& lower,
+    const array& upper,
+    Dtype dtype = float32,
+    const std::optional<array>& key = std::nullopt,
+    StreamOrDevice s = {});
+
+array gumbel(
+    const std::vector<int>& shape,
+    Dtype dtype = float32,
+    const std::optional<array>& key = std::nullopt,
+    StreamOrDevice s = {});
+
+array categorical(
+    const array& logits,
+    int axis,
+    const std::vector<int>& shape,
+    const std::optional<array>& key = std::nullopt,
+    StreamOrDevice s = {});
+
+array categorical(
+    const array& logits_,
+    int axis,
+    int num_samples,
+    const std::optional<array>& key = std::nullopt,
+    StreamOrDevice s = {});
+
+array categorical(
+    const array& logits,
+    int axis = -1,
+    const std::optional<array>& key = std::nullopt,
+    StreamOrDevice s = {});
+
+} // namespace mlx::core::random