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GeneralistOperatorPeer public scoresmeth_v0_1_1as of 2026-07-11

GPT-5.6 Sol · API · Max effort

The ecosystem operator — max-effort Sol for hard agents, not cheap chat.

OpenAI flagship Build for autonomous coding and professional workflows when ecosystem tools and max reasoning justify $5/$30.

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Codex rating
79.7
Confidence B

Overall mean of attribute public scores after peer min-max (40–95 band within scored launch peer set).

Loadout
Endpoint
gpt-5.6-sol
Product
OpenAI API
Price
$5 / $30 per MTok
Context
1000k tokens

OpenAI GPT-5.6 Sol API at max reasoning effort, 1M context, $5/$30 per MTok. Frontier generalist / coding-agent rival to Claude Opus for hard long-horizon work.

Core attributes

Six stats · peer public

Peer publicbars = rank in scored peer set (≈40–95) · raw = absolute fusion under the bar
STRExecution
94.9raw 87.9A90.998.9
DEXTempo
58.3raw 58.0B48.368.3
CONReliability
95.2raw 87.5A91.299.2
INTReasoning
94.9raw 88.5A90.998.9
WISJudgment
39.9raw 55.8A35.943.9
CHACollaboration
95.0raw 91.0B85100

Peer public (main number / bar) ranks this Build inside the current scored peer set (≈40–95). Raw is the absolute evidence-fusion aggregate before min-max. A low peer score can still be a strong absolute model — see methodology.

Practical verdict

When to choose

Best at
  • Long-horizon coding agents (named harnesses)
  • Terminal / DevOps-style multi-step work
  • Mixed professional workflows with strong tool use
Avoid for
  • Latency-first everyday chat (use lower effort or Luna/Terra)
  • Strict budget token farms
  • Trust-critical judgment without verification (high Omniscience hall pattern)
Choose this when

You want OpenAI tooling + max-effort frontier performance on hard multi-step jobs.

Skills

Task proficiencies

Test Writing96.2 A
Creative Writing91.0 B
Professional Writing91.0 B
Refactoring90.0 A
Debugging88.8 A
Devops And Terminal88.0 A
Tool Calling88.0 A
Existing Codebase Work87.0 A
Long Autonomous Runs84.0 A
Quantitative Reasoning79.7 A
Research Synthesis73.4 A
Following Complex Instructions69.1 B
Fast Interactive Work58.0 B
Traits & Quirks

Signature strengths and honest flaws

Traits · 2
Agentic Ceilingconf Binferred

Tops the independent agentic-coding boards in the scored set under max effort (leading SWE-bench Verified on named harnesses) — the highest raw coding ceiling when a hard multi-step job justifies the price.

Triggers when
  • Long-horizon coding agents with named harnesses
  • Hard multi-step engineering jobs at max effort
Tooling Nativeconf Cinferred

Strong, reliable tool and function calling with terminal / DevOps-style orchestration — comfortable driving mixed professional workflows across its ecosystem's tooling.

Triggers when
  • Terminal / DevOps multi-step work
  • Mixed professional workflows with heavy tool use
Flaws · 2
Confident Hallucinatorconf Binferredmajoroccasional

Shows an Omniscience "hallucination" pattern — states trust-critical facts confidently even when wrong, so unverified answers on judgment-heavy questions carry real risk.

Shows up when
  • Trust-critical judgment without a verification step
  • Factual claims outside provided context

Workaround · Require citations or a verification pass for trust-critical claims; keep humans or a second Build in the loop before acting on unverified facts.

Premium Output Costconf Binferredmoderatehabitual

Output pricing ($30 per MTok) is the steepest in the scored set, so max-effort runs and verbose agent loops get expensive quickly on volume.

Shows up when
  • High-volume or token-farm workloads
  • Verbose max-effort agent loops without budgets

Workaround · Reserve max-effort Sol for hard jobs; route bulk and everyday work to cheaper Builds (Grok, DeepSeek, or a lower-effort tier).

Evidence Terminal

Traceability

Every factual claim cites an evidence row. Tap a chip to see the benchmark, exact config, source, and caveats behind the number.

Engine pass meth_v0_1_1 (peer min-max vs scored launch peer set). Codex overall 79.7 (B). Attribute public scores map raw aggregates into a 40–95 band within the peer set (methodology min-max). INT uses hierarchical fusion (GPQA primary / HLE secondary / capped bleed).