DeepSeek V3.2 vs Gemini 3 Flash Preview

Pricing math on a real workload

On a 10M input / 2M output token workload, DeepSeek V3.2 costs $2.97 total; Gemini 3 Flash Preview costs $11.00. That's roughly a 3.7x gap driven by both input and output pricing. DeepSeek's OpenKey rate is $0.235664/M input and $0.353496/M output (provider price $0.2288 / $0.3432 x 1.03 fee). Gemini's OpenKey rate is $0.515/M input and $3.09/M output (provider price $0.50 / $3.00 x 1.03). The input price ratio is 0.46 — Gemini's input tokens cost more than double DeepSeek's. Gemini's completion price is where most of the workload cost difference comes from, since output tokens are priced almost 9x higher than DeepSeek's. Both models run through OpenKey on one API key with the same flat 3% fee, so the delta above is entirely provider pricing, not platform markup.

Context and modality

Gemini 3 Flash Preview supports a 1,048,576-token context window against DeepSeek V3.2's 131,072 tokens — a context ratio of 0.12, meaning DeepSeek holds about 12% of Gemini's window. If you're processing long documents, large codebases, or multi-file repos in one pass, Gemini is the only one of the two that fits. Modality is the other split: DeepSeek V3.2 is text-in/text-out only. Gemini 3 Flash Preview accepts text, image, file, audio, and video input (output stays text-only). Max output tokens are close — 64,000 for DeepSeek vs 65,535 for Gemini — so output length isn't a differentiator once you're inside DeepSeek's smaller context ceiling.

Coding and agent benchmarks

The two models were scored on different Design Arena arenas, which limits direct comparison but is informative on its own. DeepSeek V3.2 only has 'models' arena scores: codecategories elo 1213 (rank 48), website elo 1217 (rank 46), gamedev elo 1197 (rank 50), dataviz elo 1203 (rank 48). Gemini 3 Flash Preview has both 'models' scores (codecategories elo 1239 rank 33, website elo 1239 rank 33, gamedev elo 1232 rank 38 — all higher elo and better rank than DeepSeek) and a full 'agents' arena set DeepSeek has no equivalent for: fullstack elo 1130 (rank 17), webapps elo 1185 (rank 17), mobileapps elo 1188 (rank 17), godotgamedev elo 1218 (rank 8). For agentic, multi-step coding tasks, Gemini has data and DeepSeek doesn't.

Tool use and parameters

DeepSeek V3.2 exposes more inference-time control: 19 supported parameters including top_k, min_p, logprobs, top_logprobs, logit_bias, and repetition_penalty, on top of standard tools/tool_choice. Gemini 3 Flash Preview supports 11 parameters — tools, tool_choice, reasoning, response_format — but no logit-level controls. Gemini's reasoning is configurable across four effort levels (high, medium, low, minimal, default medium); DeepSeek's reasoning is a simple on/off toggle, off by default. If you need fine-grained sampling control or reasoning-effort tuning for cost/latency tradeoffs, that difference matters more than raw benchmark scores.

Questions

Which model is cheaper for a typical workload?

DeepSeek V3.2, by a wide margin. On a 10M input / 2M output token workload it costs $2.97 total versus $11.00 for Gemini 3 Flash Preview — DeepSeek's input tokens alone are priced at less than half of Gemini's per the 0.46 input price ratio.

Which has the bigger context window?

Gemini 3 Flash Preview, at 1,048,576 tokens versus DeepSeek V3.2's 131,072 tokens. That puts DeepSeek's context at roughly 12% of Gemini's size, so Gemini is the pick for long documents or large codebases in a single request.

Can DeepSeek V3.2 handle images or audio?

No. DeepSeek V3.2 is text-in/text-out only. Gemini 3 Flash Preview accepts text, image, file, audio, and video as input (output is text-only), so it's the only option here for multimodal tasks.

Does either model support tool use?

Both do — DeepSeek V3.2 and Gemini 3 Flash Preview each support tools and tool_choice parameters. Gemini also exposes four reasoning-effort levels (high, medium, low, minimal), while DeepSeek's reasoning is a simple on/off flag, disabled by default.