Claude Mythos 5.1 vs GPT-4.1
Benchmark Performance
Available Benchmarks
Technical Differences
Side-by-Side Facts
| Field | Claude Mythos 5.1 | GPT-4.1 |
|---|---|---|
| Developer | Anthropic | OpenAI |
| Family | Claude 5 1 | Gpt 4 1 |
| Model | Claude Mythos 5.1 | GPT-4.1 |
| Version | Claude Mythos 5.1 | GPT-4.1 |
| Lifecycle | active | active |
| Released | 2026-09-01 | Unknown |
| Knowledge cutoff | 2026-06-01 | 2024-06-01 |
| Input modalities | Text, Image | Text, Image |
| Output modalities | Text | Text |
| Context window | 1,000,000 | 1,047,576 |
| Total parameters | Unknown | Unknown |
| Active parameters | Unknown | Unknown |
| License | Unknown | Unknown |
| Open weights | No | No |
| API available | Yes | Yes |
| Self-hostable | No | No |
| Provider access | Anthropic (Project Glasswing) | Openai (Standard), Openrouter (Standard) |
| Capabilities | chat, generation, reasoning, tools | chat, generation, tools |
14 comparable fields · 8 material differences · Pair passes the primary-source comparison gate
Claude Mythos 5.1 Capabilities
GPT-4.1 Capabilities
Internal Comparison Graph
Related Comparisons
| A | Pair | B | Context |
|---|---|---|---|
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Claude Mythos 5.1Anthropic | vs | Claude Opus 5Anthropic | family variantsimage, text |
Claude Mythos 5.1Anthropic | vs | Claude Sonnet 5Anthropic | family variantsimage, text |
Claude Mythos 5.1Anthropic | vs | GPT-5.6 SolOpenAI | cross-developer peersimage, text |
Claude Mythos 5.1Anthropic | vs |  Gemini 3.1 ProGoogle DeepMind | cross-developer peerstext |
Claude Mythos 5.1Anthropic | vs | Grok 4.6xAI | cross-developer peersimage, text |
Claude Mythos 5.1Anthropic | vs |  Kimi-K3Moonshot AI | cross-developer peersimage, text |
Claude Mythos 5.1Anthropic | vs | Gemini 3.8 Flash CyberGoogle DeepMind | cross-developer peerstext |
GPT-4.1OpenAI | vs | GPT-5.4OpenAI | family variantsimage, text |
GPT-4.1OpenAI | vs | GPT-5.5 ProOpenAI | family variantsimage, text |
GPT-4.1OpenAI | vs | GPT-5.6 LunaOpenAI | family variantsimage, text |
Primary Evidence
Sources and Freshness
Questions
Claude Mythos 5.1 vs GPT-4.1 FAQs
Is Claude Mythos 5.1 or GPT-4.1 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Claude Mythos 5.1 and GPT-4.1, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Claude Mythos 5.1 or GPT-4.1?+
Claude Mythos 5.1 is $10.00 and GPT-4.1 is $1.00 per million tokens, so GPT-4.1 is cheaper on this metric. Claude Mythos 5.1 is $50.00 and GPT-4.1 is $4.00 per million tokens, so GPT-4.1 is cheaper on this metric.
Which has a larger context window, Claude Mythos 5.1 or GPT-4.1?+
GPT-4.1 has the larger sourced context window. Claude Mythos 5.1 supports 1,000,000 and GPT-4.1 supports 1,047,576.
Which performs better in benchmarks, Claude Mythos 5.1 or GPT-4.1?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Claude Mythos 5.1 or GPT-4.1 be self-hosted?+
Both models have the same recorded self-hosting status: unsupported. Claude Mythos 5.1 is not marked open weight; GPT-4.1 is not marked open weight.
Can Claude Mythos 5.1 and GPT-4.1 understand images?+
Claude Mythos 5.1 is documented with image input; GPT-4.1 is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Claude Mythos 5.1 or GPT-4.1?+
Claude Mythos 5.1 has the larger sourced maximum output: Claude Mythos 5.1 supports 128,000 and GPT-4.1 supports 32,768 output tokens.
Do Claude Mythos 5.1 and GPT-4.1 support reasoning and tool use?+
Claude Mythos 5.1: reasoning, tool calling, and image input. GPT-4.1: tool calling and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Claude Mythos 5.1 or GPT-4.1?+
Claude Mythos 5.1 has 1 sourced provider route; GPT-4.1 has 2, so GPT-4.1 has broader tracked availability.
Which offers better value, Claude Mythos 5.1 or GPT-4.1?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.