Which is cheaper, DeepSeek-V4-Flash-0731 or GPT-5.2?
As of August 20, 2026, DeepSeek-V4-Flash-0731 is 89% cheaper on blended LLM API pricing. DeepSeek-V4-Flash-0731 costs $0.44 per million input tokens and $1.32 per million output tokens ($1.76 blended 1M-in + 1M-out). GPT-5.2 costs $1.75 / $14.00 per million tokens ($15.75 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-V4-Flash-0731 vs GPT-5.2 cost per million tokens?
DeepSeek-V4-Flash-0731 DeepSeek API pricing is $0.44 input and $1.32 output per million tokens via DeepSeek. GPT-5.2 OpenAI API pricing is $1.75 input and $14.00 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-V4-Flash-0731 or GPT-5.2?
DeepSeek-V4-Flash-0731 leads on SWE-bench Verified: DeepSeek-V4-Flash-0731 at 88.8% vs GPT-5.2 at 80%. SWE-bench measures real GitHub fixes; LiveCodeBench measures contest programming.
What is the context window for DeepSeek-V4-Flash-0731 vs GPT-5.2?
DeepSeek-V4-Flash-0731 supports a 1M token context window, while GPT-5.2 supports 400K tokens. DeepSeek-V4-Flash-0731 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-V4-Flash-0731 or GPT-5.2?
DeepSeek-V4-Flash-0731 leads on 8 of 15 shared benchmarks versus GPT-5.2's 7 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-V4-Flash-0731 or GPT-5.2 better for production use?
Both DeepSeek-V4-Flash-0731 and GPT-5.2 are production API models. For cost-sensitive production traffic, DeepSeek-V4-Flash-0731 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-V4-Flash-0731 and GPT-5.2 in my app?
Yes. Call DeepSeek-V4-Flash-0731 through DeepSeek and GPT-5.2 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-V4-Flash-0731 vs GPT-5.2 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-V4-Flash-0731 and GPT-5.2?
DeepSeek-V4-Flash-0731 supports up to 66K output tokens per request, while GPT-5.2 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-V4-Flash-0731 or GPT-5.2?
DeepSeek-V4-Flash-0731 runs at approximately 5.860066709299238 tokens/second while GPT-5.2 runs at 100 tokens/second. GPT-5.2 is faster in raw throughput. 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-V4-Flash-0731 vs GPT-5.2 comparison?
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open DeepSeek-V4-Flash-0731 or GPT-5.2 from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.
