GPT-5.5 Pro
OpenAIKey gpt-5.5-proAlso reported as openai/gpt-5.5-pro
- Rank
- #594
- by active users
- Active users
- 1
- No change from 1 active users in the previous 30 days. vs previous 30 days
- Adoption
- 0.1%
- of 967 accounts
- Tokens
- 7.9M
- cache included
- Est. cost
- $27
- at public list prices
- First seen
- Apr 29, 2026
- in any submission
Oct 15 – Nov 13, 2026 (UTC)967 accounts100% of tokens from an identified modelData through Nov 13, 2026, 06:05 UTCHow we count
Daily active users
Distinct accounts that used this model on each UTC day.
0 active users on Nov 13, 2026
Show daily values
| Date (UTC) | Active users | Tokens |
|---|---|---|
| Oct 15, 2026 | 1 | 7.9M |
| Oct 16, 2026 | 0 | 0 |
| Oct 17, 2026 | 0 | 0 |
| Oct 18, 2026 | 0 | 0 |
| Oct 19, 2026 | 0 | 0 |
| Oct 20, 2026 | 0 | 0 |
| Oct 21, 2026 | 0 | 0 |
| Oct 22, 2026 | 0 | 0 |
| Oct 23, 2026 | 0 | 0 |
| Oct 24, 2026 | 0 | 0 |
| Oct 25, 2026 | 0 | 0 |
| Oct 26, 2026 | 0 | 0 |
| Oct 27, 2026 | 0 | 0 |
| Oct 28, 2026 | 0 | 0 |
| Oct 29, 2026 | 0 | 0 |
| Oct 30, 2026 | 0 | 0 |
| Oct 31, 2026 | 0 | 0 |
| Nov 1, 2026 | 0 | 0 |
| Nov 2, 2026 | 0 | 0 |
| Nov 3, 2026 | 0 | 0 |
| Nov 4, 2026 | 0 | 0 |
| Nov 5, 2026 | 0 | 0 |
| Nov 6, 2026 | 0 | 0 |
| Nov 7, 2026 | 0 | 0 |
| Nov 8, 2026 | 0 | 0 |
| Nov 9, 2026 | 0 | 0 |
| Nov 10, 2026 | 0 | 0 |
| Nov 11, 2026 | 0 | 0 |
| Nov 12, 2026 | 0 | 0 |
| Nov 13, 2026 | 0 | 0 |
Token mix
How the 7.9M tokens split. Cache reads are usually most of an agent's tokens and are priced far below input.
- Input62%
- Output0.4%
- Cache read37%
- Cache write0%
- Reasoning0%
Agents that carry GPT-5.5 Pro
Each agent's share of this model's tokens, and how many accounts used the model through it.
Hermes Agent100% of this model's tokens1active users
Benchmarks
The best result for GPT-5.5 Pro in each benchmark Tokscale tracks. Each benchmark has its own unit, run conditions and source, so compare a score only with other models on the same benchmark. Rank is among the models Tokscale matched in that benchmark.
- Epoch Capabilities IndexOverall · Epoch AI162.7
Epoch Capabilities Index: 162.7
- Model
- GPT-5.5 Pro
- Listed as
- GPT-5.5 Pro
- Conditions
- Not reported
- Interval
- 160.0–165.9
- Unit
- ECI
- Model released
- Apr 23, 2026
- Retrieved
- Nov 12, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Rank #14 of 158 matched modelsNo conditions reportedModel released Apr 23, 2026Source: epoch.ai (opens in a new tab) - GPQA DiamondReasoning · Epoch AI93.9%
GPQA Diamond: 93.9%
- Model
- GPT-5.5 Pro
- Listed as
- gpt-5.5-pro-pre-release_xhigh
- Conditions
- XHigh
- Unit
- % correct
- Run date
- Apr 24, 2026
- Retrieved
- Nov 12, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Near its ceiling: the top score is 96.5%, and Epoch AI estimates the reachable maximum at 97%. Differences between top models are small.
- FrontierMath Tiers 1–3 (v2)Reasoning · Epoch AI87.7%
FrontierMath Tiers 1–3 (v2): 87.7%
- Model
- GPT-5.5 Pro
- Listed as
- gpt-5.5-pro_xhigh
- Conditions
- XHigh
- Unit
- % solved
- Run date
- Jun 12, 2026
- Retrieved
- Nov 12, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Near its ceiling: the top score is 95.1%, and Epoch AI estimates the reachable maximum at 95%. Differences between top models are small.
Pricing
List prices from models.dev in US dollars per 1M tokens, retrieved Nov 12, 2026. OpenAI is the lab's own API and the reference price for the estimates below.
Price at real agent usageEstimate at list prices
What 1M tokens cost at the reference list price when they split into input, output and cache the way Tokscale users' agents used them. It is not what anyone paid.
- At this model's mix
- $30.67
- Est. per 1M tokens
37% cache reads - At the community mix
- $30.52
- Est. per 1M tokens
96% cache reads - 3:1 input/output blend
- $67.50
- Per 1M tokens at list prices
No cache
Cache reads were 37% of GPT-5.5 Pro tokens in the last 30 days and 96% of all tokens. The 3:1 blend, (3 × input + output) ÷ 4, is the usual comparison and ignores cache.
Assumptions
- OpenAI list prices per 1M tokens: input $30, output $180.
- This model's mix is its own input, output, cache and reasoning tokens in the last 30 days.
- The community mix is the tokens of every identified model in the last 30 days.
- This is an estimate at list prices, not what anyone paid.
- Reasoning tokens are priced as output.
- Long-context tiers, batch pricing and discounts are not applied.
- Token mixes come from public Tokscale submissions. Hidden accounts are excluded.
- No cache-read price is listed, so cache reads are priced as input.
- No cache-write price is listed, so cache writes are priced as input.
List prices by provider
- OpenAIReference
gpt-5.5-pro$30 input per 1M tokens$180 output per 1M tokensCache read not listedCache write not listed1.05M tokens of context - OpenRouter
openai/gpt-5.5-pro$30 input per 1M tokens$180 output per 1M tokensCache read not listedCache write not listed1.05M tokens of context - Vercel AI Gateway
openai/gpt-5.5-pro$30 input per 1M tokens$180 output per 1M tokensCache read not listedCache write not listed1M tokens of context
Specs
From models.dev (MIT), retrieved Nov 12, 2026, as the lab or the first listed provider reports them. A dash means models.dev does not list the value.
- Context window
- 1.05M tokens
- Max output
- 128K tokens
- Input
- Text, Image, PDF
- Output
- Text
- Knowledge cutoff
- Dec 1, 2025
- Release date
- Apr 23, 2026
- Open weights
- No
- Reasoning
- Yes
- Tool calling
- Yes
Top public profiles
Public profiles that used GPT-5.5 Pro most in this period, by tokens. Hidden accounts are never listed.
- 1
PROTIK MONDAL@MNDL-277.9Mtokens$27est. cost1active days$27 est. cost · 1 active days
More from OpenAI
Other OpenAI models in the same period, by active users.
- GPT-6.1 Sol70% adoption675active users
- GPT-6 Astra59% adoption575active users
- GPT-6 Luna45% adoption439active users
- Codex Auto Review30% adoption291active users
- GPT-6.1 Terra29% adoption285active users
- GPT-6 Sol25% adoption244active users
Sources and attribution
Each score keeps its own source, unit and run conditions. Tokscale does not combine benchmarks into one score, and a missing score means the model was not evaluated, not that it scored zero.