diff --git a/server/quantization.go b/server/quantization.go
index 56d882e84..5e7f45cee 100644
--- a/server/quantization.go
+++ b/server/quantization.go
@@ -21,33 +21,76 @@ type quantizer struct {
 	progressFn func(n uint64)
 }
 
+const quantizationChunkElements uint64 = 4 * 1024 * 1024
+
 func (q quantizer) WriteTo(w io.Writer) (int64, error) {
 	quantize := q.from.Kind != q.to.Kind
 	sr := io.NewSectionReader(q, int64(q.offset), int64(q.from.Size()))
 	if !quantize {
 		n, err := io.Copy(w, sr)
-		q.progressFn(q.from.Size())
+		if q.progressFn != nil {
+			q.progressFn(q.from.Size())
+		}
 		return n, err
 	}
-	data, err := io.ReadAll(sr)
-	if err != nil {
-		slog.Warn("file read error", "tensor", q.from.Name, "file", q.Name(), "error", err)
-		return 0, fmt.Errorf("unable to read tensor %s from %s: %s", q.from.Name, q.Name(), err)
+
+	if len(q.from.Shape) == 0 || q.from.Shape[0] == 0 {
+		return 0, fmt.Errorf("tensor %s has invalid shape %v", q.from.Name, q.from.Shape)
 	}
-	if uint64(len(data)) < q.from.Size() {
-		return 0, fmt.Errorf("tensor %s data size %d is less than expected %d from shape %v", q.from.Name, len(data), q.from.Size(), q.from.Shape)
+
+	fromType := fsggml.TensorType(q.from.Kind)
+	toType := fsggml.TensorType(q.to.Kind)
+	nPerRow := q.from.Shape[0]
+	totalElements := q.from.Elements()
+	if totalElements%nPerRow != 0 {
+		return 0, fmt.Errorf("tensor %s has non-row-aligned shape %v", q.from.Name, q.from.Shape)
 	}
-	var f32s []float32
-	newType := fsggml.TensorType(q.to.Kind)
-	if fsggml.TensorType(q.from.Kind) == fsggml.TensorTypeF32 {
-		f32s = unsafe.Slice((*float32)(unsafe.Pointer(&data[0])), q.from.Elements())
-	} else {
-		f32s = ggml.ConvertToF32(data, q.from.Kind, q.from.Elements())
+
+	inRowSize := fromType.RowSize(nPerRow)
+	if inRowSize == 0 {
+		return 0, fmt.Errorf("tensor %s has unsupported source type %v", q.from.Name, fromType)
 	}
-	data = ggml.Quantize(newType, f32s, q.from.Shape)
-	n, err := w.Write(data)
-	q.progressFn(q.from.Size())
-	return int64(n), err
+
+	totalRows := totalElements / nPerRow
+	rowsPerChunk := max(quantizationChunkElements/nPerRow, uint64(1))
+	chunkBuf := make([]byte, inRowSize*rowsPerChunk)
+	var written int64
+
+	for row := uint64(0); row < totalRows; {
+		chunkRows := min(rowsPerChunk, totalRows-row)
+		chunkBytes := inRowSize * chunkRows
+		data := chunkBuf[:chunkBytes]
+
+		if _, err := io.ReadFull(sr, data); err != nil {
+			slog.Warn("file read error", "tensor", q.from.Name, "file", q.Name(), "error", err)
+			return written, fmt.Errorf("unable to read tensor %s from %s: %w", q.from.Name, q.Name(), err)
+		}
+
+		var f32s []float32
+		chunkElements := chunkRows * nPerRow
+		if fromType == fsggml.TensorTypeF32 {
+			f32s = unsafe.Slice((*float32)(unsafe.Pointer(&data[0])), chunkElements)
+		} else {
+			f32s = ggml.ConvertToF32(data, q.from.Kind, chunkElements)
+		}
+
+		quantized := ggml.Quantize(toType, f32s, []uint64{nPerRow, chunkRows})
+		n, err := w.Write(quantized)
+		written += int64(n)
+		if err != nil {
+			return written, err
+		}
+		if n != len(quantized) {
+			return written, io.ErrShortWrite
+		}
+
+		if q.progressFn != nil {
+			q.progressFn(chunkBytes)
+		}
+		row += chunkRows
+	}
+
+	return written, nil
 }
 
 type quantizeState struct {