Claude Mythos vs GPT-5.4 vs Gemini 3.1 Pro: The AI Model War Just Escalated

Three days ago, Anthropic accidentally leaked its most powerful model. Now everyone wants to know: where does Claude Mythos actually land against GPT-5.4 and Gemini 3.1 Pro?

It’s the question bouncing around every AI subreddit, every developer Slack, every X thread about the leak. And it’s a surprisingly hard question to answer — because Mythos doesn’t exist in the same way GPT-5.4 and Gemini 3.1 Pro exist. You can’t use it. You can’t test it. You can only read what Anthropic’s own leaked documents claim about it, and compare those claims against what the competition has actually shipped.

That’s what this post does. No hype. Just the numbers we have, the gaps we don’t, and an honest read on what it all means.

(If you want the full story on the leak itself — the CMS error, the cybersecurity stock crash, the community reaction — we covered that in detail in our Claude Mythos deep dive.)

The Numbers Side by Side

Let’s start with what we can actually compare. Some of these numbers are confirmed benchmarks, some are from the leaked documents, and some are industry estimates. I’ve flagged which is which.

A few things jump out immediately.

First, the Mythos column is full of qualitative claims instead of numbers. “Dramatically higher” is not a benchmark score. Until Anthropic or an independent evaluator publishes actual figures, we’re comparing confirmed results against marketing language from an unfinished draft blog post.

Second, Gemini 3.1 Pro’s 94.3% on GPQA Diamond is a genuine standout. That’s PhD-level science reasoning, and it’s the highest verified score on that benchmark from any model. If Mythos beats it, that would be remarkable — but we need the number.

Third, cybersecurity is an entirely new competitive dimension. GPT-5.4 and Gemini 3.1 Pro aren’t even measured on it. Mythos isn’t just claiming to be better at an existing task — it’s claiming to define a new category.

Coding Performance

This is where most developers care, and where the comparison gets messiest.

Claude Opus 4.6 currently holds the verified crown at 80.8% on SWE-bench (single attempt). That score has held up under independent testing. If you’re building with Claude Code or using the API for code generation, Opus 4.6 is genuinely excellent — particularly for understanding large codebases, debugging, and writing production-quality code.

GPT-5.4 leads on certain coding sub-benchmarks. The specifics depend on which benchmark you’re looking at — OpenAI and independent evaluators have shown GPT-5.4 performing well on HumanEval, MBPP, and specific competitive programming tasks. MindStudio’s benchmark comparison shows the race is genuinely tight, with different models winning different categories. GPT-5.4’s strength is multi-step problem decomposition — give it a complex task and it’s particularly good at breaking it into solvable pieces.

Gemini 3.1 Pro is competitive but generally ranks third in coding-specific benchmarks. Where it shines is when you need code that integrates with Google’s ecosystem, or when the coding task benefits from its massive 2M context window — like refactoring an entire codebase at once.

Claude Mythos supposedly scores “dramatically higher” than Opus on coding. If Opus is at 80.8% and “dramatically” means even 5-10 percentage points, that would put Mythos in territory no model has reached. But those numbers don’t exist publicly yet. No independent researcher has run SWE-bench on Mythos. No developer has posted benchmark results.

What the leaked documents describe sounds more like a qualitative jump than an incremental improvement — writing, debugging, and understanding complex code at a level that makes Opus look like an earlier generation. Whether that pans out remains to be seen.

Reasoning and Science

Gemini 3.1 Pro dominates this category. Its 94.3% on GPQA Diamond (PhD-level science questions across physics, chemistry, and biology) is the highest publicly verified score. If your work involves scientific reasoning, complex multi-step math, or research synthesis, Gemini currently has no peer.

GPT-5.4 is strong on mathematical reasoning and multi-step logic. OpenAI has invested heavily in chain-of-thought reasoning, and it shows. GPT-5.4 handles problems that require holding multiple constraints in mind simultaneously — scheduling problems, optimization tasks, multi-variable analysis — with a consistency that makes it the preferred tool for many data scientists and analysts.

Claude Opus 4.6 sits around 73% on GPQA Diamond — respectable but clearly behind Gemini. Where Claude compensates is in reasoning about ambiguous problems. Give Claude a question where the “right answer” depends on interpretation, context, or nuance, and it tends to produce more thoughtful, qualified responses than models that optimize for benchmark scores.

Claude Mythos claims “dramatically higher” reasoning scores. If it closes the gap with Gemini on GPQA Diamond while maintaining Claude’s strength in nuanced reasoning, that would be a compelling combination. But again — claims from a leaked draft blog post are not verified results.

Cybersecurity: Mythos’s Unique Dimension

This is the part that moved markets and the part with no real comparison.

Anthropic’s leaked documents state that Mythos is “currently far ahead of any other AI model in cyber capabilities” and can “exploit vulnerabilities in ways that far outpace the efforts of defenders.”

GPT-5.4 and Gemini 3.1 Pro are not typically evaluated on cybersecurity benchmarks. They can assist with security tasks — code review, vulnerability scanning, explaining CVEs — but neither company has positioned their flagship model as a cybersecurity tool.

Mythos apparently operates on a different level. The implication from the leaked documents is that it can discover and exploit zero-day vulnerabilities autonomously, faster than human security teams can patch them. That’s why cybersecurity stocks dropped 3-7% the day after the leak — not because the model will necessarily be used for attacks, but because its existence implies that AI-powered offense is pulling ahead of human-led defense.

This is worth taking seriously, but also worth contextualizing. Every new capability sounds world-changing before it’s tested in the real world. Autonomous vulnerability discovery has been a research goal for years. Mythos may advance that goal significantly without achieving the apocalyptic scenarios some commentators are imagining.

For a deeper analysis of the cybersecurity implications, see our full Mythos coverage.

Context Window and Pricing

This is where things get practical — and where the available models have clear, measurable differences.

Gemini 3.1 Pro wins on two dimensions simultaneously: the largest context window (2M tokens) and the best cost efficiency. If you’re processing long documents, analyzing entire codebases, or working with extensive conversation histories, Gemini gives you the most room to work at the lowest cost.

Claude Opus 4.6’s 1M context window is still enormous — more than enough for most real-world tasks. The tradeoff is cost: at $5/$25 per million tokens, it’s significantly more expensive than Gemini for high-volume API use.

GPT-5.4’s 128K context window is the smallest of the three flagships. For most conversations and documents, 128K is fine. But if you’re feeding entire codebases or book-length documents into a model, you’ll hit the limit.

Claude Mythos pricing is unknown. The leaked documents describe it as “very expensive for us to serve, and will be very expensive for our customers to use.” Based on Anthropic’s existing pricing curve (each tier roughly doubling), speculation puts Capybara API pricing around $10-15 input / $50-75 output per million tokens. A subscription tier could be $300-500/month. But nobody knows.

Availability and Access

This is the simplest comparison and the one that matters most to anyone trying to actually use these models today.

GPT-5.4: Available now. Free tier, Plus ($20/mo), Team, Enterprise, and Pro ($200/mo) options. Largest user base of any AI model. Works through ChatGPT, API, plugins, and a massive ecosystem of third-party integrations. OpenAI’s run-rate revenue exceeds $25 billion — this is the model with the most infrastructure, the most users, and the most polish around the edges.

Gemini 3.1 Pro: Available now. Free tier and Pro ($20/mo). Deep integration with Google Workspace, Search, and the broader Google ecosystem. Native multimodal capabilities including audio and video processing. Just launched tools to import chat history from ChatGPT and Claude, aggressively pursuing user switching.

Claude Opus 4.6: Available now. Free tier, Pro ($20/mo), and Max ($100-200/mo). Strongest writing quality among all models. Growing ecosystem including Claude Code, Cowork (38+ connectors), Dispatch, Computer Use, and MCP (97M monthly downloads). Smaller market share (~2%) but highest engagement per user (34.7 minutes/day).

Claude Mythos: Not available. Early access only — restricted to cybersecurity defense organizations. No timeline for broader release. Anthropic is working to “make it much more efficient before any general release.” Could be months away. Could be longer.

This is the fundamental asymmetry in this comparison. You’re comparing two models you can use right now against one you can only read about.

The Honest Verdict

Here’s what I’d tell a friend who asked me “which one should I use?”

If Mythos didn’t exist, the honest answer would be: it depends on your work.

For coding: Claude Opus 4.6 if you want the best single-attempt accuracy, GPT-5.4 if you want the strongest problem decomposition, Gemini 3.1 Pro if you need maximum context or budget efficiency.

For science and math: Gemini 3.1 Pro. The GPQA Diamond score isn’t just a benchmark win — it translates to noticeably better performance on scientific reasoning tasks.

For writing: Claude Opus 4.6. This isn’t even close in practice. Claude produces the most natural, nuanced, human-sounding text of the three. (For a full task-by-task breakdown, see our ChatGPT vs Claude vs Gemini comparison.)

For the Google ecosystem: Gemini 3.1 Pro. If you live in Google Workspace, the native integrations are worth more than any benchmark difference.

For general daily use: GPT-5.4. The largest plugin ecosystem, the most polished consumer experience, and the widest compatibility with third-party tools.

Now add Mythos to the picture. It changes the strategic outlook but not the practical one. You can’t use Mythos today. When it becomes available — and at whatever price point Anthropic sets — it will likely be the best model for coding and possibly for reasoning. The cybersecurity angle is genuinely new territory.

But “likely” and “possibly” are doing a lot of work in that sentence. Every capability claim comes from Anthropic’s own leaked documents. No independent testing exists. The parameter estimates are rumored. The pricing is unknown.

When to Use Each

The real move for most people isn’t choosing one model. It’s learning to use the right model for the right task. These three (soon four) models are differentiated enough that switching between them based on what you’re doing will consistently outperform loyalty to any single one.

Sources:

• Fortune — Anthropic ‘Mythos’ AI model revealed in data leak
• The Decoder — Anthropic leak reveals Claude Mythos with dramatically higher scores
• CNBC — Cybersecurity stocks fall on Anthropic Mythos report
• MindStudio — GPT-5.4 vs Claude Opus 4.6 vs Gemini 3.1 Pro benchmarks