OpenAI's GPT-6 Sol and Anthropic's Opus 5.5 launched on the same day. Here is how developers should compare pricing, benchmarks, and use cases.
On September 22, 2026, OpenAI and Anthropic released competing mid-tier frontier models within hours of each other. GPT-6 Sol and Claude Opus 5.5 target the same developer audience — teams running coding agents, automation pipelines, and long-context document processing — with different pricing structures and benchmark claims.
This guide breaks down what matters for developers choosing between them.
Pricing Comparison
| Model | Input (per 1M tokens) | Output (per 1M tokens) |
|---|---|---|
| GPT-6 Sol | $2.00 | $10.00 |
| GPT-6 Luna | $0.10 | $0.50 |
| Claude Opus 5.5 | $4.00 | $20.00 |
| GPT-6 Astra | $10.00 | $50.00 |
Sol is half the price of Opus 5.5 on both input and output. For high-volume agent workloads where you process millions of tokens daily, that gap compounds quickly.
OpenAI also cut Sol and Luna API prices 50% compared to their GPT-5.6 predecessors, attributing the reduction to caching and inference improvements.
Benchmark Claims (With Caveats)
OpenAI's claims for Sol
- Agents' Last Exam V1: 56.4% at max effort, above the best Claude Opus 5 score at 60% lower cost per task.
- DeepSWE 1.1: 68.8% on long-horizon software engineering, nearly matching Claude Fable 5 at 80% lower cost.
- Factuality: Roughly half the error rate of GPT-5.6 Sol in flagged real-world conversations.
Anthropic's claims for Opus 5.5
- Matches flagship Fable on most tasks at 20% lower cost.
- Best alignment scores Anthropic has tested to date.
- Same safety safeguards as Fable in cybersecurity, biology, and AI model design.
Independent rankings
Artificial Analysis ranks Opus 5.5 #1 on its Intelligence Index (score: 58), ahead of GPT-6 Astra (53). Sol does not yet appear in independent rankings as of launch day.
Important: Neither company published direct Sol vs. Opus 5.5 head-to-head results. Cross-model benchmark comparisons use different model versions and evaluation settings.
When to Choose Sol
- Cost-sensitive agent pipelines where you run thousands of tasks daily
- Automation workflows (OpenAI's AutomationBench: 33.2% at $0.27 per task)
- Computer-use agents (OSWorld 2.0: 60.5% at xhigh effort)
- Projects where Luna's $0.10/$0.50 pricing covers simpler subtasks
When to Choose Opus 5.5
- Complex coding agents requiring maximum reasoning depth
- Long-context document analysis (Opus 5.5 offers 1M token context)
- Tasks where benchmark leadership matters more than per-token cost
- Safety-sensitive applications in cybersecurity or biology domains
Practical Recommendation
Run both models on your actual workload before committing. Vendor benchmarks use standardized evaluations that may not reflect your codebase, data formats, or task complexity.
A simple test protocol:
- Select 20 representative tasks from your production pipeline.
- Run each task on Sol and Opus 5.5 with identical prompts.
- Measure output quality (human review), latency, and total token cost.
- Calculate cost per successful task, not cost per token.
The model that wins on vendor slides may not win on your repository. Test locally, decide with data.
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