Token Demand Index

Tracked inference demand reached 116.4 trillion tokens per week as of 2026-09-27, driving the Token Demand Index to 494.9, +67% over 30 days and +395% since 2026-05-06, while the demand-weighted effective price sits at $0.72 per 1M tokens. Open-source models account for 74.7% of tracked tokens, confirming that falling unit prices reflect surging consumption rather than margin collapse as the market grows larger. It is the output-side companion to the Compute Tightness Index (the GPU input).

497Demand index (100 = 2026-05-06)
116.9TTokens / week
▲ +66%Demand, 30 days
73.3%Open-source share
$0.73Effective $/1M
$85.0MImplied spend/week*

As of 2026-09-28, tracked AI inference runs at 116.9T tokens/week — up +66% in 30 days and +397% since 2026-05-06. Open-source carries 73.3% of those tokens, holding the demand-weighted price near $0.73/1M — a fraction of frontier list prices even as frontier models themselves got pricier.

Open vs closed-model pricing

Blended price per million tokens. The closed series demand-weights each named provider group's median price by its trailing-seven-day token volume.

$0.47Open-weight models · $/1M tokens · 73.3% of tracked demand
$2.92Closed models · $/1M tokens · 7.2% of tracked demand
Open-weight $/1MClosed-model $/1M

Open-weight = the Open-source provider group. Closed = Claude, OpenAI, Google, and xAI. The unclassified “Other” bucket is excluded from the closed-model price.

⤓ Download full daily series (CSV)

Token demand vs the effective price of inference

Total tokens/weekEffective $/1M (right)

Who consumes the tokens

Open-sourceOtherClaudeOpenAIGooglexAI

By provider group — latest snapshot

Click a group to expand its top contributing models.

GroupBlended $/1MTokens/weekShare30d demand
▸Open-source$0.4785.7T73.3%▲ +67%
▸Other$0.8822.8T19.5%▲ +906%
▸Claude$6.002.0T1.7%▼ -30%
▸OpenAI$2.413.9T3.3%▼ -65%
▸Google$1.131.7T1.5%▼ -17%
▸xAI$1.56774.6B0.7%▲ +11%

Open-source = aggregated weights-available labs (DeepSeek, Qwen, Llama, Mistral, etc.). "Other" = unclassified OpenRouter providers. Share = % of tracked tokens. *Implied spend = list price × tokens, not realized revenue.

Methodology

Built from OpenRouter's model rankings + pricing, grouped into Claude / OpenAI / Google / xAI / Open-source / Other. Token counts are OpenRouter's trailing-7-day figures (the rankings "week" view) — i.e. each point is tokens processed over the prior week, not a single day. Per group: blended median $/1M (75/25 input/output) and weekly total_tokens. Demand index = latest weekly total ÷ the first week's total × 100. Effective $/1M = demand-weighted blended price (as-of prices carried forward across snapshots where only one side updated). Series since 2026-05-06; it grows as new snapshots land. Full history as CSV. Coverage is OpenRouter traffic — a large but partial slice of the market.

Pair it with the Compute Tightness Index (GPU input) for both sides of the AI-compute economy. Query the raw data from an agent via the Bargo MCP endpoint (get_inference_economics).