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
- #13
- by active users
- Active users
- 217
- Down 497 from 714 active users in the previous 30 days. vs previous 30 days
- Adoption
- 23%
- of 958 accounts
- Tokens
- 207B
- cache included
- Est. cost
- $158.3K
- at public list prices
- First seen
- Apr 14, 2026
- in any submission
Oct 14 – Nov 12, 2026 (UTC)958 accounts100% of tokens from an identified modelData through Nov 12, 2026, 00:47 UTCHow we count
Daily active users
Distinct accounts that used this model on each UTC day.
7 active users on Nov 12, 2026
Show daily values
| Date (UTC) | Active users | Tokens |
|---|---|---|
| Oct 14, 2026 | 67 | 11.3B |
| Oct 15, 2026 | 73 | 20.4B |
| Oct 16, 2026 | 59 | 10.4B |
| Oct 17, 2026 | 49 | 5.8B |
| Oct 18, 2026 | 44 | 4.5B |
| Oct 19, 2026 | 63 | 5.2B |
| Oct 20, 2026 | 54 | 12B |
| Oct 21, 2026 | 55 | 14B |
| Oct 22, 2026 | 64 | 2.6B |
| Oct 23, 2026 | 56 | 7.1B |
| Oct 24, 2026 | 53 | 12.2B |
| Oct 25, 2026 | 52 | 13.9B |
| Oct 26, 2026 | 59 | 8.7B |
| Oct 27, 2026 | 51 | 26.1B |
| Oct 28, 2026 | 48 | 12.6B |
| Oct 29, 2026 | 48 | 3.5B |
| Oct 30, 2026 | 43 | 2.7B |
| Oct 31, 2026 | 38 | 4.5B |
| Nov 1, 2026 | 33 | 2.1B |
| Nov 2, 2026 | 36 | 5.4B |
| Nov 3, 2026 | 37 | 7B |
| Nov 4, 2026 | 34 | 2.4B |
| Nov 5, 2026 | 31 | 3B |
| Nov 6, 2026 | 33 | 2.2B |
| Nov 7, 2026 | 25 | 3B |
| Nov 8, 2026 | 26 | 1.4B |
| Nov 9, 2026 | 25 | 703.4M |
| Nov 10, 2026 | 19 | 1.1B |
| Nov 11, 2026 | 19 | 1.6B |
| Nov 12, 2026 | 7 | 45.2M |
Token mix
How the 207B tokens split. Cache reads are usually most of an agent's tokens and are priced far below input.
- Input3.3%
- Output0.2%
- Cache read96%
- 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 CLI63% of this model's tokens171active users
Oh My Pi27% of this model's tokens21active users
Prime Agent4.9% of this model's tokens1active users
Senpi (OmO Native)2.2% of this model's tokens16active users
Hermes Agent2.1% of this model's tokens17active users
Gajae Code0.3% of this model's tokens1active users
OpenCode0.2% of this model's tokens6active users
Aside<0.1% of this model's tokens8active users
Pi<0.1% of this model's tokens8active users
ZCode<0.1% of this model's tokens3active users
Copilot<0.1% of this model's tokens1active users
OpenClaw<0.1% of this model's tokens2active users
Synthetic<0.1% of this model's tokens1active users
DeepSeek Harness<0.1% of this model's tokens3active users
Claude Code<0.1% of this model's tokens3active users- cc-mirror/mozilla<0.1% of this model's tokens1active users
- cc-mirror/curl<0.1% of this model's tokens1active users
9Router<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 AI162.8
Epoch Capabilities Index: 162.8
- Model
- GPT-5.6 Sol
- Listed as
- GPT-5.6 Sol
- Conditions
- Not reported
- Interval
- 160.2–167.1
- Unit
- ECI
- Model released
- Jul 9, 2026
- Retrieved
- Oct 21, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Rank #11 of 160 matched modelsNo conditions reportedModel released Jul 9, 2026Source: epoch.ai (opens in a new tab) - Terminal-Bench 4.0Agentic coding · Terminal-Bench37.3%
Terminal-Bench 4.0: 37.3%
- Model
- GPT-5.6 Sol
- Listed as
- GPT-5.6 Sol
- Conditions
- Max · Codex
- Interval
- 33.5–41.0%
- Unit
- % resolved
- Published
- Aug 27, 2026
- Retrieved
- Oct 21, 2026
Source · Terminal-Bench 4.0 official leaderboard, tbench.ai
Rank #11 of 23 matched modelsMax · CodexPublished Aug 27, 2026Source: tbench.ai (opens in a new tab)
Tokscale usage: Codex CLI carried 63% of GPT-5.6 Sol tokens in the last 30 days (171 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
- Oct 21, 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
- Oct 21, 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
- Oct 21, 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
- Oct 21, 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
- Oct 21, 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
- Oct 21, 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
- Oct 21, 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
- Oct 21, 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
- Oct 21, 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
- Oct 21, 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
- Conditions
- Max · proximus
- Unit
- mean@5
- Model released
- Jul 9, 2026
- Retrieved
- Oct 21, 2026
Source · FrontierSWE results, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Rank #9 of 21 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 63% of GPT-5.6 Sol tokens in the last 30 days (171 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
- Oct 21, 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 96.4%, 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
- Oct 21, 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
- Oct 21, 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
- Oct 21, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Near its ceiling: the top score is 93.7%, 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
- Oct 21, 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 Oct 21, 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
- $0.58
- Est. per 1M tokens
96% 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 96% of GPT-5.6 Sol 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 $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 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.
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 Oct 21, 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
szymonsec@szymonsec64.2Btokens$55.8Kest. cost16active days$55.8K est. cost · 16 active days
- 2
Kabir Acharya@KabirAcharya37.5Btokens$19.9Kest. cost20active days$19.9K est. cost · 20 active days
- 3
Junho Yeo@junhoyeo10.1Btokens$13.2Kest. cost15active days$13.2K est. cost · 15 active days
- 4
Waivey Kim@waiveyk7.8Btokens$4.2Kest. cost10active days$4.2K est. cost · 10 active days
- 5
Guanzheng Wei@GuanZhengPM7.6Btokens$8.8Kest. cost29active days$8.8K est. cost · 29 active days
- 6
Khaliq@khaliqgant6.2Btokens$3.1Kest. cost25active days$3.1K est. cost · 25 active days
- 7
joonyeonglim@joonyeonglim5.4Btokens$3.2Kest. cost15active days$3.2K est. cost · 15 active days
- 8
Kim Jin-Yeong@jinzer05.4Btokens$4.1Kest. cost24active days$4.1K est. cost · 24 active days
- 9
Wooseok Sung@MercuriusDream4.9Btokens$2.7Kest. cost6active days$2.7K est. cost · 6 active days
- 10
harris.dev@harrisrobin4.7Btokens$2.7Kest. cost14active days$2.7K est. cost · 14 active days
More from OpenAI
Other OpenAI models in the same period, by active users.
- GPT-6.1 Sol69% adoption660active users
- GPT-6 Astra59% adoption563active users
- GPT-6 Luna45% adoption433active users
- Codex Auto Review30% adoption289active users
- GPT-6.1 Terra28% adoption271active users
- GPT-6 Sol26% adoption246active 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.