Which is cheaper, Claude Mythos 5 or GPT-4 Turbo?
As of August 20, 2026, GPT-4 Turbo is 33% cheaper on blended LLM API pricing. GPT-4 Turbo costs $10.00 per million input tokens and $30.00 per million output tokens ($40.00 blended 1M-in + 1M-out). Claude Mythos 5 costs $10.00 / $50.00 per million tokens ($60.00 blended). Sources: https://platform.claude.com/docs/en/about-claude/pricing and https://developers.openai.com/api/docs/pricing. The cheapest LLM for your app still depends on how many output tokens you generate.
How much does Claude Mythos 5 vs GPT-4 Turbo cost per million tokens?
Claude Mythos 5 Claude API pricing from Anthropic is $10.00 input and $50.00 output per million tokens via Anthropic. GPT-4 Turbo OpenAI API pricing is $10.00 input and $30.00 output per million tokens via OpenAI. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Which is better for coding, Claude Mythos 5 or GPT-4 Turbo?
Claude Mythos 5 has a published SWE-bench Verified score of 95.5%. GPT-4 Turbo does not have that eval on this page yet.
What is the context window for Claude Mythos 5 vs GPT-4 Turbo?
Claude Mythos 5 supports a 1M token context window, while GPT-4 Turbo supports 128K tokens. Claude Mythos 5 offers a larger context window. Filling a larger window bills more input tokens, so the cheaper-per-million model can still cost more on long documents.
Which model performs better on benchmarks, Claude Mythos 5 or GPT-4 Turbo?
Claude Mythos 5 leads on 2 of 2 shared benchmarks versus GPT-4 Turbo's 0 wins. Check the comparison table for GPQA Diamond, SWE-bench, MMLU, HLE, and the other evals we track. Token price and benchmark score together are the usual LLM comparison, not either number alone.
Is Claude Mythos 5 or GPT-4 Turbo better for production use?
Both Claude Mythos 5 and GPT-4 Turbo are production API models. For cost-sensitive production traffic, GPT-4 Turbo has better economics on the blended 1M-in + 1M-out scale. For maximum capability, weight the benchmark table for your domain. Many production stacks route cheap models for drafts and a frontier model for the hard turn, which is usually cheaper than sending everything to the expensive API.
Can I switch between Claude Mythos 5 and GPT-4 Turbo in my app?
Yes. Call Claude Mythos 5 through Anthropic and GPT-4 Turbo through OpenAI with separate API keys, or through a gateway that already wraps both. Keep prompts in tokens, not characters, when you estimate the invoice. AnotherWrapper templates can swap providers without rewriting auth and billing.
How accurate is this Claude Mythos 5 vs GPT-4 Turbo pricing data?
List rates are the latest published Claude API pricing from Anthropic and OpenAI API pricing, quoted per million tokens. Official rate sheets: https://platform.claude.com/docs/en/about-claude/pricing and https://developers.openai.com/api/docs/pricing. Prompt caching, batch APIs, and committed-use discounts can change the invoice. Benchmark scores are from official publications and independent evals, updated as new numbers land.
What is the output token limit for Claude Mythos 5 and GPT-4 Turbo?
Claude Mythos 5 supports up to 128K output tokens per request, while GPT-4 Turbo supports up to 4K output tokens. Output tokens are usually the expensive half of API pricing, so a higher max output cap is a capability, not a discount.
Which model has better throughput, Claude Mythos 5 or GPT-4 Turbo?
GPT-4 Turbo has a measured throughput of approximately 100 tokens/second. Throughput data for Claude Mythos 5 is not yet available. Throughput (tokens per second) and time-to-first-token are why two models with the same per-million-token price can still feel different in chat and agents.
How do I switch the models in this Claude Mythos 5 vs GPT-4 Turbo comparison?
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open Claude Mythos 5 or GPT-4 Turbo from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.
