Skip to main content
BenchLM
Data

Data as of November 6, 2026 · How the score is built

Superseded.OpenAI has newer models in this line:GPT-6.1 Sol

GPT-6 Sol

Decision readingGPT-6 Sol scores 78.1 out of 100 and ranks #11 of 212. This profile shows 27 source-displayable benchmark rows; its strongest eligible category is Knowledge at #9. API pricing is $2 input and $10 output per million tokens, with cached input at $0.2.

Released Sep 22, 2026 — see all recent releases

Decision snapshot

Each value carries a field reference instead of floating alone. Markers compare this model with the current ranked and priced catalog; they are not absolute quality thresholds.

Capability

78.1/100

field median 50.1#11 of 212 ranked models

Public

#11of 212

Verified #9 of 77

Price

$2input / $10 output

input median $0.60cached $0.20 · blended $6

Speed

Not measured

field median 92 tok/sTime to first token not measured

Context

1.05Mtokens

field median 256,000Maximum output length is tracked separately

Strongest published evidence

Knowledge ranks #9. Particularly effective for knowledge-intensive tasks like research, analysis, and factual Q&A.

Validate before choosing

27 published rows leave some tracked benchmark slots empty. Independent runtime speed has not been measured.

Source-linked · 27 displayable benchmark rows

Category score record

Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.

Category scores, ranks, weighting, benchmark coverage, and evidence status
CategoryScore
Agentic10.0 points below GPT-5.6 SolRank #35 of 131Percentile 74thWeight 22%8 benchmarksVerified
57.6
Coding2.0 points below GPT-5.6 SolRank #13 of 157Percentile 92ndWeight 20%2 benchmarksVerified
65.2
ReasoningRank #12 of 25Percentile 54thWeight 17%4 benchmarksVerified
71.7
MultimodalRank Not rankedWeight 12%2 benchmarksVerified
86.6
KnowledgeRank #9 of 178Percentile 95thWeight 12%5 benchmarksVerified
80.0
MultilingualWeight 7%0 benchmarksNot measured
Not measured
Inst. FollowingWeight 5%1 benchmarkVerified
Score pending
MathRank Not rankedWeight 5%2 benchmarksVerified
93.8

An earlier release can outscore a newer one in a single category. The note under that category names the release and the gap.

27 of 816 tracked benchmark slots have displayable evidence · bars run 0–100

Coverage details

How much of this is verified

Coverage is split by category so a strong number never hides a thin evidence base. Verified means the row is tied to a published source; provisional rows remain visible but separate.

  1. Agentic8/8 verified
  2. Coding2/2 verified
  3. Reasoning4/4 verified
  4. Multimodal2/2 verified
  5. Knowledge5/5 verified
  6. MultilingualNot measured
  7. Inst. Following1/1 verified
  8. Math2/2 verified
Verified sourceProvisionalNot measured

Capability shape

Each axis shows percentile within that category’s eligible cohort. The comparison outline is the median of the six nearest public-score peers; a collapsed vertex means the category is not rank-eligible.

GPT-6 Sol category percentile values

  • Agentic74th percentile
  • Coding92nd percentile
  • Reasoning54th percentile
  • MultimodalNot eligible
  • Knowledge95th percentile
  • MultilingualNot eligible
  • Instruction followingNot eligible
  • MathNot eligible

The dashed outline is median of 6 nearest peers.

Eligible category ranks

  1. Agentic#35/131
  2. Coding#13/157
  3. Reasoning#12/25
  4. MultimodalNot ranked
  5. Knowledge#9/178
  6. MultilingualNot ranked
  7. Inst. FollowingNot ranked
  8. MathNot ranked
Top decileTop quartileMid-fieldNot eligible

Benchmark ledger

Coding opens by default. The marker compares each value with the best source-verified result in the catalog; provisional leaders do not set the reference. Expand the remaining categories for every published row.

Coding2 rows
Coding benchmark values, best verified comparison, weight, and source status
DeepSWEScore68.8%Versus best verified row

Best verified: Muse Wonder Full · 79.0%

Gap10.2 behindWeight15% ref. weight
FrontierCode 2.0Score34.3%Versus best verified row

Best verified: Claude Opus 5.5 · 45.5%

Gap11.2 behindWeightDisplay only
Agentic8 rows
Agentic benchmark values, best verified comparison, weight, and source status
AutomationBenchScore33.2%Versus best verified row

Best verified: MiniMax M3.1 Flash · 62.2%

Gap29 behindWeight6% ref. weight
Agents' Last ExamScore56.4%Versus best verified row

Best verified: GPT-6.1 Terra · 60.0%

Gap3.6 behindWeight3% ref. weight
OSWorld 2.0Score60.5%Versus best verified row

Best verified: Kimi K3.1 Pro · 79.6%

Gap19.1 behindWeightDisplay only
ExploitGymScore22.1%Versus best verified row

Best verified: Gemini 4 Carbon · 53.5%

Gap31.4 behindWeightDisplay only
CWE-bench v1Score52.0%Versus best verified row

Best verified: Gemini 4 Carbon · 71.0%

Gap19 behindWeightDisplay only
Hermes IndexHermes Index: agentic capability and cost per task inside Hermes AgentScore44.1%Versus best verified row

Best verified: Claude Opus 5.5 · 63.3%

Gap19.2 behindWeightDisplay only
Hermes BenchHermes Bench: 150 agent tasks graded on the files and state the agent leaves behindScore73.5%Versus best verified row

Best verified: Claude Opus 5.5 · 76.7%

Gap3.2 behindWeightDisplay only
MazeBenchMazeBench: visual spatial reasoning in a 3D open worldScore7%Versus best verified row

Best verified: GPT-6 Astra · 23%

Gap16 behindWeightDisplay only
Reasoning4 rows
Reasoning benchmark values, best verified comparison, weight, and source status
ARC-AGI-2Abstraction and Reasoning Corpus for AGI v2Score89.6%Versus best verified row

Best verified: GPT-6 Astra · 95%

Gap5.4 behindWeightWeighted 25%
ARC-AGI-3Abstraction and Reasoning Corpus for AGI v3Score4.6%Versus best verified row

Best verified: GPT-6 Astra · 62.7%

Gap58.1 behindWeightWeighted 15%
ARC-AGI-1ARC-AGI-1 Semi-Private EvaluationScore95.50%Versus best verified row

Best verified: Claude Fable 5 · 98.50%

Gap3 behindWeightDisplay only
ARC-AGI-3 Provider AdapterARC-AGI-3 Semi-Private: Provider Adapter harnessScore23.03%Versus best verified row

Best verified: GPT-6 Astra · 98.55%

Gap75.5 behindWeightDisplay only
Multimodal2 rows
Multimodal benchmark values, best verified comparison, weight, and source status
ExtractBench (LlamaIndex)ExtractBench: schema-guided enterprise document extraction (LlamaIndex leaderboard)Score94.57%Versus best verified row

Best verified: GPT-6.1 Sol · 95.31%

Gap0.7 behindWeightDisplay only
ParseBenchParseBench: document parsing for AI agents (LlamaIndex leaderboard)Score68.85%Versus best verified row

Best verified: Claude Opus 5.5 · 78.80%

Gap10 behindWeightDisplay only
Knowledge5 rows
Knowledge benchmark values, best verified comparison, weight, and source status
HealthBench (raw)HealthBench raw scoreScore47.1%Versus best verified row

Best verified: Claude Sonnet 5.5 · 69.4%

Gap22.3 behindWeightDisplay only
HealthBench (length-adjusted)HealthBench length-adjusted scoreScore53.2%Versus best verified row

Best verified: Claude Sonnet 5.5 · 65.4%

Gap12.2 behindWeightDisplay only
HealthBench ProfessionalScore60.8%Versus best verified row

Best verified: Claude Sonnet 5.5 · 69.2%

Gap8.4 behindWeightDisplay only
HealthBench Professional (raw)HealthBench Professional raw scoreScore59.5%Versus best verified row

Best verified: Claude Sonnet 5.5 · 77.1%

Gap17.6 behindWeightDisplay only
HealthBench HardScore30.1%Versus best verified row

Best verified: Muse Spark · 42.8%

Gap12.7 behindWeightDisplay only
Inst. Following1 row
Inst. Following benchmark values, best verified comparison, weight, and source status
Gray Swan IPI (15 attempts)Gray Swan Indirect Prompt Injection, attack success at 15 attemptsScore10.1%Versus best verified row

Best verified: Gemini 4 Carbon · 0.0%

Gap10.1 behindWeightDisplay only
Math2 rows
Math benchmark values, best verified comparison, weight, and source status
FrontierMath v2 (Tiers 1-3)FrontierMath v2 Tiers 1-3Score89.825%Versus best verified row

Best verified: GPT-6 Astra · 93.684%

Gap3.9 behindWeightWeighted 30%
FrontierMath v2 (Tier 4)FrontierMath v2 Tier 4Score90.000%Versus best verified row

Best verified: GPT-6.1 Sol · 100.000%

Gap10 behindWeightWeighted 10%
External signals3 rows
External signals benchmark values, best verified comparison, weight, and source status
SEC-Bench ProScore66.3%Versus best verified row

Best verified: Gemini 4 Carbon · 88.2%

Gap21.9 behindWeightDisplay only
ExploitBench Internal PortExploitBench — Internal Port (June–August 2026)Score5.5%Versus best verified row

Best verified: GPT-6 Cyber · 42.0%

Gap36.5 behindWeightDisplay only
ExploitGym HoneypotExploitGym Honeypot out-of-scope exploitation rateScore0.00%Versus best verified row

Best verified: GPT-6 Astra · 0.00%

GapBest verifiedWeightDisplay only

What it costs to get this score

Published API price against the public score. The x-axis uses a log scale; the dashed path marks models that are not beaten by a cheaper, higher-scoring option. Price uses average of published input and output rates.

Current modelExplore all models

GPT-6 Sol · 78.1 score · $6 blended per million tokens

The chart opens on the current model. Scroll horizontally to inspect the full price axis.

405060708090100$0.10$0.50$1$5$10$25$50$100↘ frontierGPT-6 Sol

Horizontal: blended price per million tokens, log scale · Vertical: public score

Lineage

The sequence follows explicit supersedes links. Each score is estimated for that model; a relative can inform a sparse estimate but never sets a floor, so a newer release can score below an earlier one. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.

  1. Mar 5, 2026

    GPT-5.4

    Score 66.4 · $2.5 / $15

  2. Apr 23, 2026

    GPT-5.5

    Score 68.8 · $5 / $30

  3. Jul 9, 2026

    GPT-5.6 Sol

    Score 74.8 · $4 / $20

  4. Sep 22, 2026 · you are here

    GPT-6 Sol

    Score 78.1 · $2 / $10

  5. Sep 29, 2026

    GPT-6.1 Sol

    Score 85.3 · $2 / $10

Spec sheet

Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.

Maximum output
128,000 tokensOpenAI GPT-6 Sol model documentation
Knowledge cutoff
April 20, 2026OpenAI GPT-6 Sol model documentation
Input modalities
text, imageOpenAI GPT-6 Sol model documentation
Parameters
Not disclosed by the provider
Availability
OpenAI Responses API · OpenAI Chat Completions API · ChatGPT Work · CodexOpenAI GPT-6 Sol and Luna launch

Chat Completions supports function calling with GPT-6 Sol only when reasoning_effort is none. Use the Responses API for built-in tools or for function calling with reasoning on. OpenAI GPT-6 Sol model documentation, read Sep 25, 2026

Cloud regions
Not tracked yet
API capabilities
Streaming · function calling · structured outputs · web/file search · image generation · code interpreter · hosted shell · apply patch · skills · computer use · MCP · tool searchOpenAI GPT-6 Sol model documentation
Prompt caching
Published at $0.20 per million cached input tokensOpenAI GPT-6 Sol model documentation
Self-host
Weights are not published
Rate limits
Tier 1: 500 RPM / 500K TPM; Tier 5: 15K RPM / 40M TPM; Free unsupportedOpenAI GPT-6 Sol model documentation

How to read this profile

The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.

GPT-6 Sol ranks #11 of 212 on the public leaderboard with a score of 78.09/100. Its source-verified position is #9 of 77.

GPT-6 Sol is a proprietary model with a 1.05M context window. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.

Released September 22, 2026 in ChatGPT Work and Codex for Plus, Pro, Business, Enterprise, and Edu users, and in the OpenAI API as gpt-6-sol. OpenAI documents Responses API support for built-in tools and function calling; Chat Completions supports function calling when reasoning_effort is set to none.

OpenAI documents GPT-6 Sol as a distinct API model for complex coding and agentic workflows, with configurable reasoning, text and image input, text output, and a 1,050,000-token context window. OpenAI publishes provider-run measurements, and ARC Prize provides verified ARC-AGI results.

GPT-6 Sol sits in the GPT-6 family with GPT-6 Astra, GPT-6.1 Sol, GPT-6.1 Terra, GPT-6 Luna, GPT-6 Cyber. Its explicit predecessor is GPT-5.6 Sol. 27 of 816 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.

Its strongest eligible category is Knowledge at #9, while its lowest eligible position is Agentic at #35. particularly effective for knowledge-intensive tasks like research, analysis, and factual Q&A.

Last updated November 6, 2026. Runtime fields remain blank until a sourced snapshot exists.

Deployment options

Self-host and provider-specific paths stay separate from benchmark evidence so operating constraints are visible before a score becomes the whole decision.

Where to run GPT-6 Sol by API

OpenRouter is the one host we track that publishes a per-token price for it. Prices read from each host’s own pages on October 20, 2026.

Inference hosts for GPT-6 Sol with input, output and cached-input prices per million tokens.
HostInput /1MOutput /1MCached /1MContext
OpenRouter$2.00$10.00$0.201.05M
Compare inference hosts

Questions

How does GPT-6 Sol perform overall in AI benchmarks?

GPT-6 Sol ranks #11 out of 212 models on the public BenchAlign leaderboard, with a score of 78.09/100. Its evidence status is Supported, and this profile shows 27 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.

Is GPT-6 Sol good for knowledge and understanding?

GPT-6 Sol ranks #9 out of 178 eligible models for knowledge and understanding, with a public category score of 80/100. That places it in the current top ten for this category. Check the underlying rows before treating the aggregate as a workload guarantee.

Is GPT-6 Sol good for coding and programming?

GPT-6 Sol ranks #13 out of 157 eligible models for coding and programming, with a public category score of 65.2/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Is GPT-6 Sol good for mathematics?

GPT-6 Sol has source-displayable benchmark coverage for mathematics, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.

Is GPT-6 Sol good for reasoning and logic?

GPT-6 Sol ranks #12 out of 25 eligible models for reasoning and logic, with a public category score of 71.7/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Is GPT-6 Sol good for agentic tool use and computer tasks?

GPT-6 Sol ranks #35 out of 131 eligible models for agentic tool use and computer tasks, with a public category score of 57.6/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Is GPT-6 Sol good for multimodal and grounded tasks?

GPT-6 Sol has source-displayable benchmark coverage for multimodal and grounded tasks, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.

Is GPT-6 Sol good for instruction following?

GPT-6 Sol has source-displayable benchmark coverage for instruction following, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.

Which sibling models are related to GPT-6 Sol?

GPT-6 Sol belongs to the GPT-6 family. Related tracked variants include GPT-6 Astra, GPT-6.1 Sol, GPT-6.1 Terra, plus 2 more. A sibling link indicates shared lineage or a documented configuration relationship; it does not mean the variants have identical pricing, context limits, benchmark evidence, or deployment behavior. Compare before switching.

Does GPT-6 Sol have full benchmark coverage on BenchLM?

No. GPT-6 Sol currently has 43 source-displayable rows. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.

What is the context window size of GPT-6 Sol?

GPT-6 Sol has a documented context window of 1.05M. That figure is the maximum combined prompt and retained-conversation space reported for this exact model; it is not the maximum output length. The profile keeps output limits separate because providers often publish those limits independently.

Watch GPT-6 Sol in the weekly brief

Get one weekly email when material rank, price, availability, or benchmark evidence changes are worth revisiting.

Read a sample issue

Join 6,100+ subscribers.

Compare GPT-6 Sol with every tracked model1015 comparisons