Which is cheaper, DeepSeek-V3.1 or GPT-5.1 Codex High?
As of August 20, 2026, DeepSeek-V3.1 is 89% cheaper on blended LLM API pricing. DeepSeek-V3.1 costs $0.27 per million input tokens and $1.00 per million output tokens ($1.27 blended 1M-in + 1M-out). GPT-5.1 Codex High costs $1.25 / $10.00 per million tokens ($11.25 blended). Sources: https://api-docs.deepseek.com/quick_start/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 DeepSeek-V3.1 vs GPT-5.1 Codex High cost per million tokens?
DeepSeek-V3.1 DeepSeek API pricing is $0.27 input and $1.00 output per million tokens via DeepSeek. GPT-5.1 Codex High OpenAI API pricing is $1.25 input and $10.00 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, DeepSeek-V3.1 or GPT-5.1 Codex High?
DeepSeek-V3.1 has a published SWE-bench Verified score of 66%. GPT-5.1 Codex High does not have that eval on this page yet.
What is the context window for DeepSeek-V3.1 vs GPT-5.1 Codex High?
DeepSeek-V3.1 supports a 164K token context window, while GPT-5.1 Codex High supports 400K tokens. GPT-5.1 Codex High 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, DeepSeek-V3.1 or GPT-5.1 Codex High?
GPT-5.1 Codex High leads on 1 of 1 shared benchmarks versus DeepSeek-V3.1'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 DeepSeek-V3.1 or GPT-5.1 Codex High better for production use?
Both DeepSeek-V3.1 and GPT-5.1 Codex High are production API models. For cost-sensitive production traffic, DeepSeek-V3.1 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 DeepSeek-V3.1 and GPT-5.1 Codex High in my app?
Yes. Call DeepSeek-V3.1 through DeepSeek and GPT-5.1 Codex High 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 DeepSeek-V3.1 vs GPT-5.1 Codex High pricing data?
List rates are the latest published DeepSeek API pricing and OpenAI API pricing, quoted per million tokens. Official rate sheets: https://api-docs.deepseek.com/quick_start/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 DeepSeek-V3.1 and GPT-5.1 Codex High?
DeepSeek-V3.1 supports up to 164K output tokens per request, while GPT-5.1 Codex High supports up to 128K 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, DeepSeek-V3.1 or GPT-5.1 Codex High?
GPT-5.1 Codex High has a measured throughput of approximately 50 tokens/second. Throughput data for DeepSeek-V3.1 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 DeepSeek-V3.1 vs GPT-5.1 Codex High comparison?
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open DeepSeek-V3.1 or GPT-5.1 Codex High from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.
