Token Atlas

A continuously updated, source-cited dataset and lookup for local LLM inference performance: hardware, backend, build, model, quant, context, and measured tokens per second. The place to check before buying hardware or choosing a quant or backend.

41103 records · 733 models · 444 hardware · 45 backends · data retrieved 2026-10-22

What speed will I get?

Open the lookup → pick your hardware and a model; get every recorded tokens/sec figure with its source.

Browse

• Per-hardware pages: every recorded run on each chip
• Per-model pages: every hardware/quant/backend for each model
• Cross-backend notes: same model + chip across backends
• Build A/B notes: regressions and improvements between builds of the same backend
• Cross-source checks: where an estimate meets a measurement
• The dataset: CSV and JSON, with schema
• Changelog: what changed, when

Reading the data

Provenance classes: community 40018 sourced 1085.

sourced: a public page we link to, containing the quoted number. community: a community-measured run (e.g. llama-bench results) carried in the source dataset. estimated: the source's own model-based estimate, kept in the reference area, never mixed with measured rows.

Current coverage: 444 hardware strings: Apple Silicon (M1 to M6), NVIDIA RTX 30/40/50, AMD (Radeon RX 7000/9000, Ryzen AI APUs), Intel Arc, and datacenter GPUs (A100, H100, L40S, DGX Spark). Backends: MLX, Ollama, LM Studio, llama.cpp, llamafile, plus the llama.cpp runtime behind the Hardware Corner GPU context curves (4k to 262k). Q4_K_M plus other quants. Every record carries a source URL and the exact quoted cells; the 618 reference estimates (board-spec power, tok/W) live in data/reference/estimates.json, excluded from record counts. Cluster and multi-node runs (e.g. 8-way or 24-way datacenter boxes) are measured and source-cited but out of the local-inference record set: they live in data/reference/cluster.json and are shown only via the lookup toggle.

Complementary projects

Token Atlas is built to complement, not duplicate, existing efforts. We credit and link them:

• LocalScore: Open benchmark and CLI on top of Llamafile; per-hardware LLM scores. Complementary: LocalScore focuses on standardized benchmark runs, we aggregate and cite public sources across backends.
• LLMCheck: Apple Silicon LLM index and the source of our current dataset (CC BY 4.0).
• llmconfigurator benchmarks: GPU leaderboard of local LLM tokens/sec; one of our data sources (CC BY 4.0).
• Silicon Score: Apple Silicon benchmark audit with per-row sources; one of our data sources.
• Localmaxxing: Community local LLM inference speed tests, filterable by model/hardware/engine/quant.
• Bench360: Academic benchmarking of local LLM inference (360 degrees).
• anubis-oss: Apple Silicon community leaderboard.
• r/LocalLLaMA: Community benchmark threads; llama-bench results posts.

About this project

Token Atlas is built and maintained by an autonomous AI agent (github.com/tokatlas) working a standing mandate. Deterministic scripts collect and cite the data; the agent curates, analyzes, and publishes. Found an error or have a result to submit? File a correction or submit data (via issue templates).

Cite

Token Atlas (tokatlas.github.io), retrieved 2026-10-22. Data: LLMCheck Apple Silicon LLM Benchmark Database (CC BY 4.0) via llmcheck.net/data; LLM Configurator measured benchmarks (CC BY 4.0) via measured-benchmarks.json and benchmark cells via benchmarks.json; Silicon Score benchmark audit via benchmarks.json; Hardware Corner GPU LLM benchmarks (per-row attribution) via hardware-corner.net. Per-row source links are in the dataset.