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AI Business & Economics · Index
LLM TOKEN PRICE INDEX 2026
The price of a given level of AI capability is collapsing faster than almost any technology in history — roughly an order of magnitude per year. Every figure is linked to its primary source and dated.
Key takeaways
- ~280× in ~2 years. A GPT-3.5-level system fell from $20.00 per million tokens (Nov 2022) to $0.07 (Oct 2024). (Stanford HAI)
- “LLMflation.” Cost to reach a fixed capability bar drops roughly 10× per year; Epoch AI finds task-specific declines up to ~50×/yr. (a16z / Epoch)
- Frontier prices fall slower. The cliff is in capability-per-dollar, not the sticker price of the newest model.
- Falling token costs are the engine behind agentic and test-time-compute workloads — use cases uneconomic in 2023 are routine by 2026.
280×
~10×/yr
$0.07
The capability-cost curve
The clearest single series comes from Stanford HAI’s AI Index 2025, which tracks the inference price of reaching GPT-3.5 performance (MMLU 64.8) over time. The decline is steep and roughly log-linear — the cost to run a GPT-3.5-class model fell more than 280× in about two years, from $20.00 per million tokens in November 2022 to $0.07 in October 2024 (Stanford HAI AI Index 2025).
| Period | GPT-3.5-level inference cost ($/1M tokens) |
|---|---|
| Nov 2022 | $20.00 |
| Aug 2023 | $1.80 |
| Jun 2024 | $0.18 |
| Oct 2024 | $0.07 |
“The cliff is in capability-per-dollar, not the sticker price of the newest model.”
Current frontier API pricing
Below is current published API pricing per 1M tokens. Anthropic’s figures are confirmed against the provider’s own pricing; other vendors’ list prices vary and should be confirmed against each provider’s pricing page before relying on them.
| Model | Input ($/1M) | Output ($/1M) | Confidence |
|---|---|---|---|
| Anthropic Claude Opus 4.8 | $5.00 | $25.00 | High |
| Anthropic Claude Sonnet 4.6 | $3.00 | $15.00 | High |
| Anthropic Claude Haiku 4.5 | $1.00 | $5.00 | High |
| Other frontier vendors (OpenAI, Google, DeepSeek, xAI) | List prices vary; confirm on each provider’s page | Vendor-listed |
Why “price per token” understates the drop
Capability is rising at the same time. A dollar buys both cheaper tokens and a more capable model, so cost-per-useful-task falls faster than cost-per-token. Open-weight models reset the floor — competitive open models (DeepSeek, Llama-class) pull hosted prices down across the board. And frontier is the exception: the newest top model is priced for willingness-to-pay; the deflation shows up once a capability tier becomes commoditized.
The numbers in full
| Indicator | Value | Source |
|---|---|---|
| GPT-3.5-level inference cost (Nov 2022) | $20.00 / 1M | Stanford HAI |
| GPT-3.5-level inference cost (Oct 2024) | $0.07 / 1M | Stanford HAI |
| Total decline, GPT-3.5-class | >280× | Stanford HAI |
| Cost decline at fixed capability | ~10×/yr | a16z |
| Task-specific cost decline (longer run) | up to ~50×/yr | Epoch AI |
| Claude Opus 4.8 (input / output) | $5.00 / $25.00 | Anthropic |
Frequently asked
How fast are AI inference costs falling?
For a fixed capability level, roughly 10× per year per a16z; Stanford HAI documents a ~280× fall for GPT-3.5-class inference between November 2022 and October 2024. (a16z / Stanford HAI)
Does this mean frontier models are getting cheaper?
Not as quickly. The steep decline applies to reaching a given capability bar. The newest frontier models hold their price longer; deflation hits a tier once cheaper or open-weight models match it.
What does a GPT-3.5-level system cost today?
About $0.07 per million tokens as of October 2024, down from $20.00 in November 2022 — a more than 280× decline. (Stanford HAI)
Cite this page
The AI Index (2026). LLM Token Price Index 2026. Retrieved Jun 20, 2026, from report-ai.org/indexes/ai-economics/llm-token-price-index/
Related: AI Business & Economics · Compare year over year · Tokens · Large Language Model
On this page
- Key takeaways
- The capability-cost curve
- Frontier API pricing
- Why per-token understates
- The numbers in full
- Frequently asked
- Cite this page
Primary sources
- Stanford HAI — AI Index 2025. GPT-3.5-level capability-cost curve
- a16z / Epoch AI — LLMflation. ~10×/yr · up to ~50×/yr task-specific
- Anthropic — provider pricing, Jun 2026. Claude Opus / Sonnet / Haiku
280×
Drop in GPT-3.5-class inference cost in under two years — $20.00 to $0.07 per 1M tokens.
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