GPT-5.6 Sol
OpenAIKey gpt-5.6-solAlso reported as router_client:codex/gpt-5.6-sol, codex/gpt-5.6-sol, cx/gpt-5.6-sol, openai/gpt-5.6-sol, chatgpt-web/gpt-5.6-sol, kiro/gpt-5.6-sol, openai codex/gpt-5.6-sol, azure-openai/gpt-5.6-sol, main/gpt-5.6-sol, cursor/gpt-5.6-sol, anthropic/codex/gpt-5.6-sol, eai/gpt/gpt-5.6-sol, azure-foundry/gpt-5.6-sol, gpt-5.6 sol, a6/gpt-5.6-sol, auto/gpt-5.6-sol, combo/gpt-5.6-sol, gpt/gpt-5.6-sol, router_client:unknown/gpt-5.6-sol, cbai/gpt-5.6-sol
- Rank
- #12
- by active users
- Active users
- 61
- Down 26 from 87 active users in the previous 7 days. vs previous 7 days
- Adoption
- 10%
- of 610 accounts
- Tokens
- 10.3B
- cache included
- Est. cost
- $6.6K
- at public list prices
- First seen
- Apr 14, 2026
- in any submission
Nov 6–12, 2026 (UTC)610 accounts100% of tokens from an identified modelData through Nov 12, 2026, 08:05 UTCHow we count
Daily active users
Distinct accounts that used this model on each UTC day.
9 active users on Nov 12, 2026
Show daily values
| Date (UTC) | Active users | Tokens |
|---|---|---|
| Nov 6, 2026 | 33 | 2.2B |
| Nov 7, 2026 | 25 | 3B |
| Nov 8, 2026 | 26 | 1.6B |
| Nov 9, 2026 | 26 | 734.3M |
| Nov 10, 2026 | 20 | 1.1B |
| Nov 11, 2026 | 20 | 1.6B |
| Nov 12, 2026 | 9 | 63.9M |
Token mix
How the 10.3B tokens split. Cache reads are usually most of an agent's tokens and are priced far below input.
- Input2.3%
- Output0.2%
- Cache read97%
- Cache write<0.1%
- Reasoning<0.1%
Agents that carry GPT-5.6 Sol
Each agent's share of this model's tokens, and how many accounts used the model through it.
Codex CLI82% of this model's tokens46active users
Senpi (OmO Native)10% of this model's tokens3active users
Hermes Agent4.6% of this model's tokens10active users
Gajae Code2.2% of this model's tokens1active users
ZCode0.4% of this model's tokens1active users
Pi<0.1% of this model's tokens1active users
Oh My Pi<0.1% of this model's tokens1active users
OpenCode<0.1% of this model's tokens1active users
Synthetic<0.1% of this model's tokens1active users- cc-mirror/mozilla<0.1% of this model's tokens1active users
- cc-mirror/curl<0.1% of this model's tokens1active users
Benchmarks
The best result for GPT-5.6 Sol 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. Agent rows also show Tokscale usage through that agent, side by side with the score. Usage does not explain the score.
- Epoch Capabilities IndexOverall · Epoch AI163.0
Epoch Capabilities Index: 163.0
- Model
- GPT-5.6 Sol
- Listed as
- GPT-5.6 Sol
- Conditions
- Not reported
- Interval
- 160.7–165.5
- Unit
- ECI
- Model released
- Jul 9, 2026
- Retrieved
- Nov 12, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Rank #13 of 158 matched modelsNo conditions reportedModel released Jul 9, 2026Source: epoch.ai (opens in a new tab) - Terminal-Bench 4.1Agentic coding · Terminal-Bench38.5%
Terminal-Bench 4.1: 38.5%
- Model
- GPT-5.6 Sol
- Listed as
- GPT-5.6 Sol
- Conditions
- Max · Codex
- Interval
- 34.6–42.3%
- Unit
- % resolved
- Published
- Nov 3, 2026
- Retrieved
- Nov 12, 2026
Source · Terminal-Bench 4.1 official leaderboard, tbench.ai
Tokscale usage: Codex CLI carried 82% of GPT-5.6 Sol tokens in the last 7 days (46 active users). - CursorBenchAgentic coding · Cursor, collected by Epoch AI41.7%
CursorBench: 41.7%
- Model
- GPT-5.6 Sol
- Listed as
- GPT-5.6 Sol Max
- Conditions
- Max
- Unit
- score
- Model released
- Jul 9, 2026
- Retrieved
- Nov 12, 2026
Best of 5 reported results for this model.
Source · CursorBench results by Cursor, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Show 4 more results with other run conditionsHide the other results
- Listed as GPT-5.6 Sol Extra High37.7%
CursorBench: 37.7%
- Model
- GPT-5.6 Sol
- Listed as
- GPT-5.6 Sol Extra High
- Conditions
- XHigh
- Unit
- score
- Model released
- Jul 9, 2026
- Retrieved
- Nov 12, 2026
Source · CursorBench results by Cursor, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- Listed as GPT-5.6 Sol High35.7%
CursorBench: 35.7%
- Model
- GPT-5.6 Sol
- Listed as
- GPT-5.6 Sol High
- Conditions
- High
- Unit
- score
- Model released
- Jul 9, 2026
- Retrieved
- Nov 12, 2026
Source · CursorBench results by Cursor, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- Listed as GPT-5.6 Sol Medium31.1%
CursorBench: 31.1%
- Model
- GPT-5.6 Sol
- Listed as
- GPT-5.6 Sol Medium
- Conditions
- Medium
- Unit
- score
- Model released
- Jul 9, 2026
- Retrieved
- Nov 12, 2026
Source · CursorBench results by Cursor, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- Listed as GPT-5.6 Sol Low24.6%
CursorBench: 24.6%
- Model
- GPT-5.6 Sol
- Listed as
- GPT-5.6 Sol Low
- Conditions
- Low
- Unit
- score
- Model released
- Jul 9, 2026
- Retrieved
- Nov 12, 2026
Source · CursorBench results by Cursor, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- DeepSWEAgentic coding · Datacurve, collected by Epoch AI72.7%
DeepSWE: 72.7%
- Model
- GPT-5.6 Sol
- Listed as
- gpt-5-6-sol (max)
- Conditions
- Max · mini-swe-agent
- Interval
- 69.8–75.5%
- Unit
- pass@1
- Model released
- Jul 9, 2026
- Retrieved
- Nov 12, 2026
Best of 5 reported results for this model.
Source · DeepSWE results by Datacurve, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Rank #4 of 26 matched modelsMax · mini-swe-agentModel released Jul 9, 2026Source: deepswe.datacurve.ai (opens in a new tab)Show 4 more results with other run conditionsHide the other results
- Listed as gpt-5-6-sol (xhigh)70.7%
DeepSWE: 70.7%
- Model
- GPT-5.6 Sol
- Listed as
- gpt-5-6-sol (xhigh)
- Conditions
- XHigh · mini-swe-agent
- Interval
- 69.9–71.6%
- Unit
- pass@1
- Model released
- Jul 9, 2026
- Retrieved
- Nov 12, 2026
Source · DeepSWE results by Datacurve, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- Listed as gpt-5-6-sol (high)69.4%
DeepSWE: 69.4%
- Model
- GPT-5.6 Sol
- Listed as
- gpt-5-6-sol (high)
- Conditions
- High · mini-swe-agent
- Interval
- 68.0–70.8%
- Unit
- pass@1
- Model released
- Jul 9, 2026
- Retrieved
- Nov 12, 2026
Source · DeepSWE results by Datacurve, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- Listed as gpt-5-6-sol (medium)61.1%
DeepSWE: 61.1%
- Model
- GPT-5.6 Sol
- Listed as
- gpt-5-6-sol (medium)
- Conditions
- Medium · mini-swe-agent
- Interval
- 59.5–62.6%
- Unit
- pass@1
- Model released
- Jul 9, 2026
- Retrieved
- Nov 12, 2026
Source · DeepSWE results by Datacurve, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- Listed as gpt-5-6-sol (low)45.4%
DeepSWE: 45.4%
- Model
- GPT-5.6 Sol
- Listed as
- gpt-5-6-sol (low)
- Conditions
- Low · mini-swe-agent
- Interval
- 43.0–47.7%
- Unit
- pass@1
- Model released
- Jul 9, 2026
- Retrieved
- Nov 12, 2026
Source · DeepSWE results by Datacurve, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- FrontierSWEAgentic coding · FrontierSWE, collected by Epoch AI32.2%
FrontierSWE: 32.2%
- Model
- GPT-5.6 Sol
- Listed as
- GPT-5.6 Sol
- Conditions
- Max · proximus
- Unit
- mean@5
- Model released
- Jul 9, 2026
- Retrieved
- Nov 12, 2026
Source · FrontierSWE results, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Rank #11 of 23 matched modelsMax · proximusModel released Jul 9, 2026Source: frontierswe.com (opens in a new tab) - WebDev ArenaWeb development · LMArena1,616
WebDev Arena: 1,616
- Model
- GPT-5.6 Sol
- Listed as
- GPT-5.6 Sol (xHigh, Codex Harness)
- Conditions
- XHigh · Codex
- Interval
- 1610–1622
- Unit
- Arena score
- Published
- Oct 19, 2026
- Retrieved
- Oct 21, 2026
Source · LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset on Hugging Face), CC BY 4.0
Rank #24 of 110 matched modelsXHigh · CodexPublished Oct 19, 2026Source: huggingface.co (opens in a new tab)
Tokscale usage: Codex CLI carried 82% of GPT-5.6 Sol tokens in the last 7 days (46 active users). - Agent ArenaAgents · LMArena+0.07
Agent Arena: +0.07
- Model
- GPT-5.6 Sol
- Listed as
- GPT-5.6 Sol (xHigh)
- Conditions
- XHigh · Arena Agent Mode
- Interval
- 0.05 to 0.08
- Unit
- net improvement
- Published
- Oct 19, 2026
- Retrieved
- Oct 21, 2026
Source · LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset on Hugging Face), CC BY 4.0
Rank #10 of 48 matched modelsXHigh · Arena Agent ModePublished Oct 19, 2026Source: huggingface.co (opens in a new tab) - GPQA DiamondReasoning · Epoch AI93.5%
GPQA Diamond: 93.5%
- Model
- GPT-5.6 Sol
- Listed as
- gpt-5.6-sol_max
- Conditions
- Max
- Unit
- % correct
- Run date
- Jul 9, 2026
- Retrieved
- Nov 12, 2026
Best of 3 reported results for this model.
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.
Show 2 more results with other run conditionsHide the other results
- Listed as gpt-5.6-sol_low89.9%
GPQA Diamond: 89.9%
- Model
- GPT-5.6 Sol
- Listed as
- gpt-5.6-sol_low
- Conditions
- Low
- Unit
- % correct
- Run date
- Aug 7, 2026
- Retrieved
- Nov 12, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- Listed as gpt-5.6-sol_none82.8%
GPQA Diamond: 82.8%
- Model
- GPT-5.6 Sol
- Listed as
- gpt-5.6-sol_none
- Conditions
- No reasoning
- Unit
- % correct
- Run date
- Aug 7, 2026
- Retrieved
- Nov 12, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- FrontierMath Tiers 1–3 (v2)Reasoning · Epoch AI89.1%
FrontierMath Tiers 1–3 (v2): 89.1%
- Model
- GPT-5.6 Sol
- Listed as
- gpt-5.6-sol_max
- Conditions
- Max
- Unit
- % solved
- Run date
- Jul 9, 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.
- SimpleQA VerifiedKnowledge · Epoch AI69.7%
SimpleQA Verified: 69.7%
- Model
- GPT-5.6 Sol
- Listed as
- gpt-5.6-sol_max
- Conditions
- Max
- Unit
- % correct
- Run date
- Aug 10, 2026
- Retrieved
- Nov 12, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
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
- $0.54
- Est. per 1M tokens
97% cache reads - At the community mix
- $0.61
- Est. per 1M tokens
96% cache reads - 3:1 input/output blend
- $8
- Per 1M tokens at list prices
No cache
Cache reads were 97% of GPT-5.6 Sol tokens in the last 7 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 $4, output $20, cache read $0.40, cache write $5.
- This model's mix is its own input, output, cache and reasoning tokens in the last 7 days.
- The community mix is the tokens of every identified model in the last 7 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.
List prices by provider
- OpenAIReference
gpt-5.6-sol$4 input per 1M tokens$20 output per 1M tokens$0.40 cache read per 1M tokens$5 cache write per 1M tokens1.05M tokens of context - Amazon Bedrock
openai.gpt-5.6-sol$4.40 input per 1M tokens$22 output per 1M tokens$0.44 cache read per 1M tokens$5.50 cache write per 1M tokens1.05M tokens of context - Azure
gpt-5.6-sol$4 input per 1M tokens$20 output per 1M tokens$0.40 cache read per 1M tokens$5 cache write per 1M tokens1.05M tokens of context - OpenRouter
openai/gpt-5.6-sol$4 input per 1M tokens$20 output per 1M tokens$0.40 cache read per 1M tokens$5 cache write per 1M tokens1.05M tokens of context - Vercel AI Gateway
openai/gpt-5.6-sol$4 input per 1M tokens$20 output per 1M tokens$0.40 cache read per 1M tokens$5 cache write per 1M tokens1.05M 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
- Feb 16, 2026
- Release date
- Jul 9, 2026
- Open weights
- No
- Reasoning
- Yes
- Tool calling
- Yes
Top public profiles
Public profiles that used GPT-5.6 Sol most in this period, by tokens. Hidden accounts are never listed.
- 1
Khaliq@khaliqgant2.9Btokens$1.5Kest. cost6active days$1.5K est. cost · 6 active days
- 2
harris.dev@harrisrobin2.3Btokens$1.2Kest. cost2active days$1.2K est. cost · 2 active days
- 3
Chaewan Kim@amsminn1Btokens$585est. cost2active days$585 est. cost · 2 active days
- 4
Guanzheng Wei@GuanZhengPM683Mtokens$693est. cost7active days$693 est. cost · 7 active days
- 5
Waivey Kim@waiveyk598.6Mtokens$326est. cost2active days$326 est. cost · 2 active days
- 6
Park Hee Chan@channprj317.8Mtokens$391est. cost6active days$391 est. cost · 6 active days
- 7
Wooseok Sung@MercuriusDream308Mtokens$159est. cost1active days$159 est. cost · 1 active days
- 8
우종호@Woo-JongHo276.4Mtokens$213est. cost7active days$213 est. cost · 7 active days
- 9
Borel@Keonho-Chu266.6Mtokens$176est. cost3active days$176 est. cost · 3 active days
- 10
Zhoeyi@zaozhiyi253.4Mtokens$135est. cost6active days$135 est. cost · 6 active days
More from OpenAI
Other OpenAI models in the same period, by active users.
- GPT-6.1 Sol58% adoption351active users
- GPT-6 Astra44% adoption269active users
- GPT-6 Luna25% adoption154active users
- GPT-6.1 Terra22% adoption137active users
- Codex Auto Review18% adoption112active users
- GPT-6 Sol8.7% adoption53active 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.