deepseek-v3.1 vs gpt-5 — cost comparison

Together AI deepseek-v3.1 vs OpenAI gpt-5 — list pricing, worked examples, interactive calculator. Verified 2026-05-15.

TL;DR. deepseek-v3.1 is cheaper on both input (8.3×) and output (11.8×).

Headline pricing

	deepseek-v3.1	gpt-5
Input / 1M tokens	$0.60	$5.00
Output / 1M tokens	$1.70	$20.00
Cache write / 1M tokens	—	—
Cache read / 1M tokens	—	$0.50

Sources: Together AI, OpenAI. Verified 2026-05-15. Re-verify before relying on these numbers for budget commits.

Worked examples (per call, list pricing)

Workload shape	deepseek-v3.1	gpt-5	Cheaper
1k in + 500 out (tool call)	$0.0014	$0.0150	deepseek-v3.1 (10.3× cheaper)
10k in + 1k out (RAG)	$0.0077	$0.0700	deepseek-v3.1 (9.1× cheaper)
100k in + 1k out (long doc)	$0.0617	$0.520	deepseek-v3.1 (8.4× cheaper)
2k in + 4k out (long gen)	$0.0080	$0.0900	deepseek-v3.1 (11.3× cheaper)

Interactive calculator

Calls per month

Prompt tokens / call

Completion tokens / call

(reserved)

How to choose between deepseek-v3.1 and gpt-5

Quality first. Cost only matters if both models clear your quality bar. Run a 30-call eval on real prompts before committing to the cheaper option. If quality is unequal, the price difference is a distraction.
Match price to call shape. deepseek-v3.1 costs $0.60 in / $1.70 out. gpt-5 costs $5.00 in / $20.00 out. Workloads that are completion-heavy weigh output prices more.
Caching changes the math. gpt-5 cache-read is $0.50. If your prompts have a stable prefix, the model with the better cache discount typically wins on re-use.
Latency may matter more than dollars. Some providers are 5-10× faster at the same price tier. If you're below a few thousand calls/day, latency UX usually beats price.

Track what you're actually spending on each

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Related comparisons

Together AI full pricing · OpenAI full pricing · All-provider comparison

About this page. Built and maintained by an autonomous AI agent under KS Elevated Solutions LLC. Pricing data comes from each provider's published pricing page, verified 2026-05-15; the same table is bundled in the tokenmark npm package. No fabricated reviews, ratings, or social proof. See full AI disclosure.