API

Static JSON for scripts, dashboards, and AI agents. No auth required.

Static JSON only (no query API). Same files for automation and humans. CC BY 4.0 — attribute ComputeNav when redistributing.

Quick start

Load in order:

  1. llms.txt — short machine-oriented overview.
  2. index.json — version, endpoints, license, generated_at.
  3. models.json — meta + entries (one object per hosted offer).
  4. site_news.json — optional curated outbound links for the Models News card (items[] with title, url, source, date, summary, keywords[]).
  5. models_catalog.json — mirror of models_catalog.csv (includes optional model_intro per model for Models).
  6. indicators.json — manually curated proxy metrics for AI compute supply/demand (used by Indicators).
  7. firms_prices.json — daily/delayed public-company market snapshot for Firms; informational only, not investment advice.

Use source_url on each entry to answer “where did this price come from?”. All figures are indicative; confirm with the provider before buying or relying on SLAs.

Task Weigh — describe a workload, estimate tokens (Claude Haiku 4.5 via a small proxy), and compare indicative provider costs using the same models.json data.

index.json

version 2: includes shards (paths to per-modality JSON) and totals.n_entries / totals.by_shard. Legacy clients can still use endpoints.models → models.json (chat / text panel). Empty shards: image_models.json, video_models.json, embedding_models.json.

Also: endpoints (including indicators → indicators.json), note, documentation, gcpi, license, generated_at.

models.json shape

{
  "meta": {
    "generated_at": "…",
    "methodology_version": "0.2.0",
    "snapshot_date": "YYYY-MM-DD",
    "n_entries": 0,
    "n_providers": 0,
    "source": "computenav.com",
    "license": "CC BY 4.0"
  },
  "entries": [ { … }, … ]
}

Each entries item = one row in the panel (one offer).

Entry fields (per offer)

Field Meaning
model_label Human-readable model name from the provider.
model_id Provider-specific id or slug.
model_developer Organization that released the weights (e.g. Meta, OpenAI).
model_release_date Public release date YYYY-MM-DD (curated).
model_parameters Stated parameter scale (e.g. 70B, 671B) or —.
capability_score / capability_metric Optional capability signal: numeric capability_score plus capability_metric = lmsys_elo (Chatbot Arena Elo), mmlu, humaneval, mt_bench, composite, or other. Do not rank across different metrics as if they were one scale.
quantization_precision Quantization precision for served weights (e.g. FP16/BF16 (typical), Not disclosed).
model_type Lowercase tags, comma-separated: chat, vision, reasoning, image, video, audio, etc.
model_source open | closed | unknown (weights availability).
compute_provider / provider Host / API vendor (same value twice for compatibility).
price_per_1m_input / price_per_1m_output USD per 1M tokens (numbers).
price_blended Default table sort is model_release_date descending (newest models first); click column headers to re-sort.
modality / pricing_unit modality: chat | image | video | embedding. pricing_unit: e.g. per_1m_tokens, per_image, per_second.
price_usd_per_image Image rows: USD per image (empty for other modalities).
price_usd_per_video_second Video rows: USD per second of output (empty elsewhere).
price_usd_per_1m_embedding_input Embedding rows: USD per 1M input tokens (empty elsewhere).
latency_ms / throughput_tps Indicative performance (not live benchmarks).
context_window Max context in tokens.
openai_compatible Boolean — OpenAI-style chat/completions on api_base_url.
endpoint Primary product or vendor URL.
api_base_url OpenAI-compatible API base if applicable.
developer_website / provider_website Official sites for model author and host.
region Hosting geography (lowercase): us, eu, asia, uk, global, or ISO 3166-1 alpha-2 (e.g. de, jp).
geo_fencing Short geographic fence / residency tag (summary; verify with vendor).
data_privacy_no_train Data privacy and training policy — curated note; always confirm vendor terms.
source_url Pricing source for verification.
fetched_at / source / price_snapshot_date Row lineage and snapshot date.
status healthy | degraded | etc.

Example: fetch in JavaScript

const base = new URL("../api/v1/", window.location.href);
const res = await fetch(new URL("models.json", base));
const { meta, entries } = await res.json();
const openCheap = entries
  .filter((e) => e.model_source === "open")
  .sort((a, b) => a.price_blended - b.price_blended)[0];

Filtering & ranking

Public shards omit rows with status of pending, down, or error (they remain in the curated CSV for audit). Sort and filter entries in your code for other needs. The public site applies its own client-side keyword logic for search; you can mirror that behavior or implement your own.

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