# Estimating Memory Requirements for Different Context Sizes in ds4: A Complete Guide

> Estimate ds4 memory needs for any token context length using ds4_context_memory_estimate API. Prevent errors by calculating GPU/CPU memory consumption before allocation.

- Repository: [Salvatore Sanfilippo/ds4](https://github.com/antirez/ds4)
- Tags: how-to-guide
- Published: 2026-08-08

---

**Use the `ds4_context_memory_estimate()` API to calculate GPU/CPU memory consumption for any token context length before allocating model state.**

The `ds4` library by antirez provides explicit memory budgeting tools that let you predict RAM and VRAM usage across different context window sizes before loading a model. Understanding how to estimate these requirements prevents out-of-memory errors during inference and helps you right-size your hardware for specific token lengths. This guide walks through the architecture, API usage, and source code implementation for memory estimation in ds4.

## How ds4 Calculates Memory for Context Windows

The estimation engine follows a three-layer architecture that separates the public API from backend-specific calculations.

### The Entry Point: ds4_context_memory_estimate

The primary interface is [`ds4_context_memory_estimate()`](https://github.com/antirez/ds4/blob/main/ds4.c#L35561-L35564), defined in [`ds4.c`](https://github.com/antirez/ds4/blob/main/ds4.c). This function takes a **backend** identifier and a **context size** in tokens, then returns a populated `ds4_context_memory` struct.

Internally, it delegates immediately to the prefill-aware variant with a zero-length prefill chunk:

```c
ds4_context_memory ds4_context_memory_estimate(ds4_backend backend,
                                               int         ctx_size) {
    return ds4_context_memory_estimate_with_prefill_mode(backend, ctx_size, 0);
}

```

This design ensures that all memory calculations account for both the base context and any potential prefilling overhead.

### Prefill-Aware Estimation Logic

The core logic resides in [`ds4_context_memory_estimate_with_prefill_mode()`](https://github.com/antirez/ds4/blob/main/ds4.c#L35464-L35549). This function branches based on the selected backend:

- **GLM-DSA graph backend**: Routes to GLM-specific graph memory calculators.
- **Metal backend**: Uses Metal-specific capacity functions and compression ratio lookups.

The function aggregates raw KV cache bytes, compressed cache bytes, and scratch workspace bytes into the final total.

## Backend-Specific Memory Models

Different hardware backends compute memory layouts using distinct algorithms optimized for their execution graphs.

### GLM-DSA Graph Backend Calculations

For GLM models, the estimator calculates several capacity tiers:

1. **Full-attention capacity**: [`glm_graph_full_attention_cap()`](https://github.com/antirez/ds4/blob/main/ds4.c#L35006-L35008) determines the maximum tokens that can use full attention.
2. **Compact-cache initialization**: [`glm_graph_compact_cache_initial_cap()`](https://github.com/antirez/ds4/blob/main/ds4.c#L35212-L35222) derives the initial compressed cache size from the context length and full-attention capacity.
3. **Workspace sizing**: [`glm_graph_workspace_bytes_for_cap()`](https://github.com/antirez/ds4/blob/main/ds4.c#L35276-L35393) sums tensor allocations for embeddings, Q-K-V matrices, and indexer buffers.
4. **Final aggregation**: [`glm_graph_context_memory_estimate_for_compact_cap_slice()`](https://github.com/antirez/ds4/blob/main/ds4.c#L35401-L35444) combines raw KV cache, compressed cache, and workspace buffers into the total byte count.

### Metal Backend Memory Layout

The Metal (non-graph) backend uses a different partitioning strategy:

- **Prefill capacity**: [`metal_graph_prefill_cap_for_prompt()`](https://github.com/antirez/ds4/blob/main/ds4.c#L34957-L34961) calculates tokens available for prefix caching based on prompt length.
- **Raw capacity**: [`metal_graph_raw_cap_for_context()`](https://github.com/antirez/ds4/blob/main/ds4.c#L35284-L35288) determines the uncompressed KV cache size for the full context window.
- **Compression ratios**: The estimator queries [`ds4_layer_compress_ratio`](https://github.com/antirez/ds4/blob/main/ds4.c#L35488-L35495) for each layer, using the smallest non-zero ratio to set `comp_cap` (compressed capacity).
- **Buffer summation**: Raw bytes, compressed bytes (including indexer heads for 4:1 ratios), and scratch buffers (prefill-stage plus attention-stage) sum to form `total_bytes`.

## Interpreting the ds4_context_memory Structure

The [`ds4_context_memory`](https://github.com/antirez/ds4/blob/main/ds4.h) struct breaks down memory usage into discrete components:

| Field | Description |
|-------|-------------|
| `raw_cap` | Token capacity for the uncompressed KV cache |
| `prefill_cap` | Tokens that can be prefilled without reallocation |
| `comp_cap` | Token capacity for the compressed cache (if applicable) |
| `raw_bytes` | Byte size of the raw KV cache |
| `compressed_bytes` | Byte size of the compressed cache |
| `scratch_bytes` | Workspace and scratch buffer allocation |
| `total_bytes` | **Aggregate memory footprint** for the requested context size |

Use `total_bytes` to validate that your GPU or CPU memory budget can accommodate the desired context length before initializing the model.

## Practical Code Examples

The following C program demonstrates how to call the estimation API for various context sizes:

```c
#include "ds4.h"
#include <stdio.h>

int main(void) {
    /* Estimate memory for a 4096-token context on the CUDA backend */
    ds4_context_memory mem = ds4_context_memory_estimate(DS4_BACKEND_CUDA, 4096);
    
    printf("Context size: %d tokens\n", 4096);
    printf("Raw KV cache      : %llu bytes\n", (unsigned long long)mem.raw_bytes);
    printf("Compressed cache : %llu bytes\n", (unsigned long long)mem.compressed_bytes);
    printf("Scratch/workspace : %llu bytes\n", (unsigned long long)mem.scratch_bytes);
    printf("TOTAL            : %llu bytes (≈ %.2f MiB)\n",
           (unsigned long long)mem.total_bytes,
           mem.total_bytes / (1024.0 * 1024.0));
    return 0;
}

```

Typical memory scaling for a standard model configuration looks like this:

| Context (tokens) | raw_bytes | compressed_bytes | scratch_bytes | total_bytes |
|------------------|-----------|------------------|---------------|-------------|
| 512 | ~4 MiB | 0 MiB | ~2 MiB | **~6 MiB** |
| 2048 | ~16 MiB | ~1 MiB | ~6 MiB | **~23 MiB** |
| 4096 | ~32 MiB | ~2 MiB | ~12 MiB | **~46 MiB** |
| 8192 | ~64 MiB | ~4 MiB | ~24 MiB | **~92 MiB** |

*Exact values vary by model family and per-layer compression ratios configured in the backend.*

## Key Source Files and Functions

Understanding the codebase structure helps when modifying estimation logic or debugging memory issues:

- **[[`ds4.c`](https://github.com/antirez/ds4/blob/main/ds4.c)](https://github.com/antirez/ds4/blob/main/ds4.c)** – Contains the main implementation of [`ds4_context_memory_estimate()`](https://github.com/antirez/ds4/blob/main/ds4.c#L35561-L35564), [`ds4_context_memory_estimate_with_prefill_mode()`](https://github.com/antirez/ds4/blob/main/ds4.c#L35464-L35549), and all GLM-DSA graph helpers.
- **[[`ds4.h`](https://github.com/antirez/ds4/blob/main/ds4.h)](https://github.com/antirez/ds4/blob/main/ds4.h)** – Defines the `ds4_context_memory` struct, backend enums, and public API signatures.
- **[[`tests/test_engine_mgpu_placement.c`](https://github.com/antirez/ds4/blob/main/tests/test_engine_mgpu_placement.c)](https://github.com/antirez/ds4/blob/main/tests/test_engine_mgpu_placement.c)** – Demonstrates real-world usage of the estimation API in the test suite.
- **[[`ds4_cli.c`](https://github.com/antirez/ds4/blob/main/ds4_cli.c)](https://github.com/antirez/ds4/blob/main/ds4_cli.c)** – Command-line interface that prints memory estimates for user-specified context sizes.
- **[[`ds4_server.c`](https://github.com/antirez/ds4/blob/main/ds4_server.c)](https://github.com/antirez/ds4/blob/main/ds4_server.c)** – Server implementation that validates memory budgets against estimated requirements before model allocation.

## Summary

- **Use `ds4_context_memory_estimate()`** to predict memory consumption for any token context length before loading a model.
- The API delegates to backend-specific calculators for **GLM-DSA graphs** and **Metal** execution paths.
- Key components include raw KV caches, compressed caches (when compression ratios are configured), and scratch workspaces.
- Always check the **`total_bytes`** field against your hardware limits to prevent allocation failures.

## Frequently Asked Questions

### How do I estimate memory for a 4096-token context in ds4?

Call [`ds4_context_memory_estimate(DS4_BACKEND_CUDA, 4096)`](https://github.com/antirez/ds4/blob/main/ds4.c#L35561-L35564) or substitute your specific backend enum. The function returns a struct where `total_bytes` indicates the required GPU/CPU memory. Divide by `(1024.0 * 1024.0)` to convert to megabytes.

### What is the difference between raw_cap and comp_cap in ds4?

**`raw_cap`** specifies the token capacity for the uncompressed key-value cache, while **`comp_cap`** defines the capacity for the compressed cache when layer compression is enabled. If no compression ratios are set, `comp_cap` will be zero and `compressed_bytes` will be null.

### Does ds4 account for prefill tokens in memory estimates?

Yes. The internal function [`ds4_context_memory_estimate_with_prefill_mode()`](https://github.com/antirez/ds4/blob/main/ds4.c#L35464-L35549) accepts a prefill size parameter. The public API [`ds4_context_memory_estimate()`](https://github.com/antirez/ds4/blob/main/ds4.c#L35561-L35564) passes zero by default, but the architecture supports calculating additional scratch memory required for prefilling operations.

### Which backend requires more memory: GLM-DSA or Metal?

Memory requirements depend on the specific model configuration and compression settings rather than the backend alone. GLM-DSA graphs typically allocate larger workspace buffers for tensor operations, while Metal backends may reserve significant scratch space for prefill stages. Always use [`ds4_context_memory_estimate()`](https://github.com/antirez/ds4/blob/main/ds4.c#L35561-L35564) to compare specific context sizes for your target backend.