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Last updated: October 21, 2026
Which model wins the Claude Opus 5.5 vs GPT-6 Sol matchup for enterprise agents? Claude Opus 5.5 leads on independent capability scores and resists prompt injection better, while GPT-6 Sol costs half as much per token and roughly a sixth as much per task on one index. Both launched in September 2026, so most numbers are still vendor-reported.
TL;DR: Key Takeaways
- Claude Opus 5.5 scores 58 on the Artificial Analysis Intelligence Index at max effort, against 48 for GPT-6 Sol.
- GPT-6 Sol lists at $2 input and $10 output per million tokens, half of Opus 5.5's $4 and $20.
- On that index Opus 5.5 used 260M output tokens at $5.98 per task, while Sol used 77M at $1.04, a gap above 5x.
- On Gray Swan's indirect prompt injection test, attacks succeed 1.0% of the time against Opus 5.5 and 10.1% against Sol within 15 attempts, per provider-reported results.
- On AutomationBench, Anthropic reports 40.0% for Opus 5.5 and OpenAI reports 33.2% for Sol at $0.27 per task.
- OpenAI has since shipped GPT-6.1 Sol, which it says beats Opus 5.5 on AutomationBench by 2.2 points at medium effort.
At a Glance: Claude Opus 5.5 vs GPT-6 Sol
| Spec | Claude Opus 5.5 | GPT-6 Sol |
|---|---|---|
| Vendor and release | Anthropic, September 22, 2026 | OpenAI, September 2026 |
| API model ID | claude-opus-5-5 | gpt-6-sol |
| Context window | 1M tokens | 1.05M tokens |
| Max output | 128K tokens | 128K tokens |
| Input / output price per 1M tokens | $4 / $20 | $2 / $10 |
| Reasoning control | Adaptive, always on, effort low to max | Effort none to max |
| Artificial Analysis Intelligence Index | 58 | 48 |
| Gray Swan IPI success (15 attempts) | 1.0% | 10.1% |
Specs and API Differences
Both models offer about 1M tokens of context and 128K tokens of output, so window size does not separate them. The differences sit in how you control reasoning, how tool calling behaves and how pricing scales on long prompts. Opus 5.5 always thinks adaptively, while GPT-6 Sol lets you switch reasoning off.
Reasoning and tool calling
According to the Claude Platform docs, thinking on Opus 5.5 cannot be disabled, code that turns it off fails, and forcing a specific tool through tool_choice returns an error. Default effort is medium. In the OpenAI model docs, Sol supports effort none, low, medium (default), high, xhigh and max. Chat Completions allows function calling only with effort set to none, so reasoning plus tools requires the Responses API.
Long prompts and safeguards
Sol doubles input and cache rates and multiplies output by 1.5 for prompts above 272K input tokens. Anthropic's model page lists a single Opus 5.5 price. Anthropic also notes that production safeguards reroute some work: cybersecurity tasks complete on Opus 4.8, and biology and frontier model development tasks on Opus 5. Log which model served each request.
Availability and lifecycle
Opus 5.5 runs on the Claude API, Amazon Bedrock, Google Cloud and Microsoft Foundry, with retirement not sooner than September 22, 2027. Artificial Analysis lists OpenAI and Microsoft Azure as GPT-6 Sol providers, and OpenAI's page shows one snapshot, gpt-6-sol, now marked as superseded. Pin versions and plan a retest whenever a vendor ships a point release.
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Claude Opus 5.5 vs GPT-6 Sol Benchmarks
Opus 5.5 leads every head-to-head number published so far, but most come from the vendors. Independent testing shows a smaller gap on agentic coding than Anthropic's launch table does. Treat the rows below as vendor-reported unless marked independent, and check the notes before comparing them.
| Benchmark | Claude Opus 5.5 | GPT-6 Sol | Note |
|---|---|---|---|
| Intelligence Index | 58 | 48 | Independent, max effort |
| AutomationBench | 40.0% | 33.2% | Different runs, vendor-reported |
| Terminal-Bench 4.0 | 66.4% | Not published | Anthropic, xhigh effort |
| OSWorld | 81.8% (2.1) | 60.5% (2.0 offline) | Not comparable |
| DeepSWE v1.1 | Not published | 68.8% | OpenAI, max effort |
Where the gap is real
Artificial Analysis measured Opus 5.5 at 59.6% on Terminal-Bench 4.0, 6.8 points under Anthropic's 66.4%. Even so, the 10-point Intelligence Index gap comes from an independent run. The OSWorld rows use different benchmark versions and scoring, so ignore the 21-point difference.
Where it narrows
OpenAI's GPT-6.1 Sol announcement says the upgrade scores 2.2 points above Opus 5.5 on AutomationBench at medium effort for about a third of the cost. That is a vendor claim. It still means the Sol line now competes on agent workflows, not only on price. Read it as a reason to retest, since Sol results are dated September 2026.
How we compared
We used vendor documentation for specs and prices, Artificial Analysis for independent scores and provider self-reports for security. We ran no tests of our own.
Agent Workflows, Speed and Effort Settings
Effort settings change results more than model choice does. Artificial Analysis shows GPT-6 Sol rising from 34 on the Intelligence Index at low effort to 48 at max, with cost per task varying up to 7.9x across variants and bottoming out at $0.13 on low. Opus 5.5 exposes the same trade-off through its effort setting, with medium as the default.
OpenAI reports Sol at max effort scoring 56.4% on Agents' Last Exam at 60% lower cost per task than Opus 5's top result. That compares Sol with the previous Opus, so it says little about Opus 5.5. On speed, Artificial Analysis measured 95.4 output tokens per second for Opus 5.5 and 117.7 for Sol at max effort. Anthropic also sells a fast mode for Opus 5.5 at $8 input and $40 output per million tokens, up to 2.5x faster.
Set effort per workload, not per model. Start both at medium, measure cost per resolved task, and raise effort only where accuracy pays for itself.
Pricing and Cost per Task
GPT-6 Sol costs half as much per token as Opus 5.5 and used about a third of the output tokens on Artificial Analysis's index. Opus 5.5 buys more capability per task, but a Sol agent loop can cost a fraction as much. Cost per task decides most production choices, so model it before you commit.
| Scenario (list price, no caching) | Claude Opus 5.5 | GPT-6 Sol |
|---|---|---|
| 100K input + 10K output tokens | $0.60 | $0.30 |
| 600K input + 20K output tokens | $2.80 | $2.70 |
| Average cost per Intelligence Index task | $5.98 | $1.04 |
The long-prompt row shows why surcharges matter. Sol's discount shrinks to $0.10 once the 272K threshold applies. Both models price cached input at $0.20 per million tokens, so cache hit rate matters more than list price in long agent loops. Batch discounts of 50% apply on both platforms.
Security and Governance: Prompt Injection and Tool Risk
Prompt injection tops the OWASP Top 10 for LLM Applications as LLM01. Opus 5.5 shows a lower injection success rate than Sol in provider-reported results, but no model score replaces runtime controls on agents that read email, web pages and tool output.
Anthropic says Opus 5.5 ties Claude Fable 5.1 for the lowest prompt injection success rate among the models it tested. BenchLM lists 1.0% for Opus 5.5 and 10.1% for GPT-6 Sol on Gray Swan's test at 15 attempts. All rows are self-reported, and the attack set is unpublished. OpenAI's Deployment Safety Hub reports 99.99% instruction hierarchy compliance for Sol and rates it High in cybersecurity and biology, below Critical for cyber. Instruction hierarchy and injection success are different measures.
| Risk | What the data says | Control that still matters |
|---|---|---|
| Indirect prompt injection | Opus 5.5 1.0%, Sol 10.1% (self-reported) | Inspect tool results before the model sees them |
| Tool misuse | No model score covers it | Allow-list tools, least privilege per agent |
| Data leakage | Not measured in these benchmarks | Redact and log prompts and outputs |
| Silent model switching | Opus 5.5 safeguards reroute some tasks | Log the serving model per request |
Model scores do not cover tool misuse or data leakage once an agent has live access. For deeper reading, see our Claude Opus 5.5 enterprise security analysis and the GPT-6 Astra security implications. In practice, put an Agent Gateway (TrustGate) between agents and models, with 200+ pre-built MCP servers behind policy. Add Agent Runtime Security (TrustGuard) to inspect tool results for planted instructions. Routing both models through one control point also lets you A/B test them safely.
Which Should You Choose?
| Your situation | Better fit | Why |
|---|---|---|
| Quality first: agentic coding, computer use | Claude Opus 5.5 | Leads the independent index |
| High volume, cost per task decides | GPT-6 Sol or 6.1 Sol | Half the token price, fewer tokens |
| Agents read untrusted email, web, tickets | Claude Opus 5.5 | Lower reported injection success |
| Low-latency function calling with reasoning off | GPT-6 Sol | Effort none keeps tools simple |
| Multi-cloud procurement | Claude Opus 5.5 | Offered on Claude Platform, Amazon Bedrock, Google Cloud and Microsoft Foundry |
A mixed setup is common in practice. Teams send planning, review and untrusted-content tasks to Opus 5.5, and send summarization, extraction and routine tool calls to Sol or GPT-6.1 Sol. Whatever you pick, define the routing rule in policy so it can change without a code release.
Conclusion
In the Claude Opus 5.5 vs GPT-6 Sol comparison, Opus 5.5 is the stronger and safer model on published evidence, and Sol is the cheaper one per task. Most teams will not choose one forever. Route hard, high-risk work to Opus 5.5 and bulk work to Sol or GPT-6.1 Sol, then retest quarterly because vendor numbers move fast.
Secure Claude Opus 5.5 and GPT-6 Sol in Production with NeuralTrust
Run both models behind one gateway with policy, logging and injection checks, and switch between them without rewriting agents.
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Related Comparisons
- Claude vs ChatGPT (2026): Benchmarks, Pricing & Verdict
- GPT-6 Sol vs Luna
- Gemini 4 Argon vs Claude Opus 5.5
FAQs about Claude Opus 5.5 vs GPT-6 Sol
1. Is Claude Opus 5.5 better than GPT-6 Sol?
On published evidence, yes for capability and prompt injection resistance. Opus 5.5 scores 58 against Sol's 48 on the Artificial Analysis Intelligence Index. Sol costs far less per task, so "better" depends on whether accuracy or spend is your constraint.
2. How much do Claude Opus 5.5 and GPT-6 Sol cost?
Opus 5.5 costs $4 per million input tokens and $20 per million output tokens. GPT-6 Sol costs $2 and $10. Both charge $0.20 per million cached input tokens, and prompts above 272K tokens cost more on Sol.
3. What is the context window of each model?
Opus 5.5 offers 1M tokens and GPT-6 Sol offers 1.05M. Both allow 128K tokens of output, so context size should not decide the choice.
4. Is GPT-6 Sol still the current OpenAI model?
No. OpenAI's model page points to GPT-6.1 Sol as the newer Sol model. GPT-6 Sol remains available in the API, but its September 2026 results predate the upgrade, so retest before you decide.
5. Which model is safer against prompt injection?
Opus 5.5, based on provider-reported Gray Swan results: 1.0% attack success against 10.1% for Sol at 15 attempts. Treat those figures as indicative, since the attack set is unpublished.
6. Can I use both models in one application?
Yes. A gateway can route each request by task, cost or risk and apply the same security policy to both. That avoids vendor lock-in and lets you shift traffic when pricing or benchmarks change.
7. Which model is better for coding agents?
Anthropic reports 66.4% for Opus 5.5 on Terminal-Bench 4.0, and Artificial Analysis measured 59.6%. OpenAI reports 68.8% for Sol on DeepSWE v1.1. The benchmarks differ, so run both on your own repositories before choosing.
About the Author
Roger Howroyd is Head of Global SEO and AI at NeuralTrust, where he leads the company's search strategy across SEO, AEO, GEO, and LLM optimization. He specializes in AI-powered search, content strategy, and SEM. Connect on LinkedIn.
NeuralTrust is the leading platform for securing and scaling AI agents. Named a Pioneer in the Gartner Emerging Market Quadrant for AI Application Security 2026, recognized across four Gartner Hype Cycle reports in 2026, and featured in the Gartner Market Guide for Guardian Agents 2026, the Gartner Market Guide for AI Gateways 2025 and the KuppingerCole Leadership Compass for Generative AI Defense 2025. Headquartered in Barcelona with offices in London and New York. ISO 27001 certified.
Sources
- Anthropic, Introducing Claude Opus 5.5, September 22, 2026
- Claude Platform Docs, Claude Opus 5.5
- OpenAI, Introducing GPT-6 Sol and Luna, September 2026
- OpenAI API Docs, GPT-6 Sol Model
- OpenAI, Introducing GPT-6.1 Sol
- OpenAI Deployment Safety Hub, GPT-6 Sol and GPT-6 Luna: October 2026 update, October 7, 2026
- Artificial Analysis, Claude Opus 5.5
- Artificial Analysis, GPT-6 Sol
- BenchLM, Gray Swan IPI (15 attempts) leaderboard, updated October 20, 2026
- OWASP, LLM01: Prompt Injection
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