DeepSeek-V4-Pro vs Gemini 3.8 Flash
DeepSeek-V4-Pro wins on Overall, Coding; Gemini 3.8 Flash wins on Multimodal. Every numeric field is compared below, with a worked monthly-cost example and a pick rule for each use case.
Verdict at a glance
Choose DeepSeek-V4-Pro if you…
- Strongest open source
- Value champion
- Excellent math reasoning
- Extremely low price
- Best for: Coding, Math reasoning, Open-source deployment
Choose Gemini 3.8 Flash if you…
- Best-coding Flash yet
- Native text/image/audio/video
- Very fast and low-priced
- Stronger agentic reasoning
- Best for: Fast tasks, Multimodal, Coding
Head-to-head aggregate scores
Scores are 0–100, aggregated from public benchmark information and independently weighted across three leaderboards. Rank is out of 26 tracked models.
Aggregated from public sources and independently weighted; methodology on the Terms page. Scores within 3 points are treated as statistically tied.
Specs & pricing — every field side by side
List API prices in USD per 1M tokens. The highlighted cell is the stronger value/capability on that row.
| Dimension | DeepSeek-V4-Pro | Gemini 3.8 Flash | Verdict |
|---|---|---|---|
| Vendor | DeepSeek (CN) | Google (US) | Different vendors |
| Released | 2026.04 | 2026.09 | Gemini 3.8 Flash is newer |
| Overall (rank) | 77 · #10 | 73 · #12 | DeepSeek-V4-Pro +4 |
| Coding | 79 · #8 | 73 · #13 | DeepSeek-V4-Pro +6 |
| Multimodal | 77 · #16 | 88 · #9 | Gemini 3.8 Flash +11 |
| Context window | 1M | 1M | Tie |
| Max output | 128K | 64K | Gemini 3.8 Flash longer |
| Effective-context | 94 | 90 | DeepSeek-V4-Pro more reliable |
| Input $/1M | $0.44 | $0.75 | DeepSeek-V4-Pro cheaper |
| Output $/1M | $1.32 | $3.75 | DeepSeek-V4-Pro cheaper |
| Cache discount | none | none | Tie |
| Speed | ~70 tok/s | ~85 tok/s | Gemini 3.8 Flash faster |
| TTFT | 0.5s | 0.3s | Gemini 3.8 Flash snappier |
| Function calling | 82 | 78 | DeepSeek-V4-Pro ahead |
| Refusal rate | ~5% | ~10% | DeepSeek-V4-Pro less restrictive |
| English | 82 | 88 | Gemini 3.8 Flash |
| Chinese | 85 | 74 | DeepSeek-V4-Pro |
| Modalities | text | text, image, audio, video | different coverage |
| Open weights | Yes | No | DeepSeek-V4-Pro is open |
| Fine-tuning | Yes | Yes | |
| Free tier | DeepSeek App free; new API users receive credits | Gemini App free; API free tier; intro price through Dec 31, 2026 | |
| SOC2 / no-train | no / yes | yes / yes | |
| Private deployment | Yes | No | DeepSeek-V4-Pro |
Fields drawn from vendor public documentation and the Modelspectra 26-model dataset; speed varies with network, concurrency and prompt length. Verify current pricing before purchase.
Dimension-by-dimension analysis
Reasoning & overall intelligence
DeepSeek-V4-Pro leads the overall aggregate by 4 points (77 vs 73). That is a meaningful, not marginal, edge on hard, multi-step reasoning, while Gemini 3.8 Flash remains a strong generalist that is not out of its depth on routine work.
Agentic coding
This is a modest gap: DeepSeek-V4-Pro scores 79 against 73. On multi-file edits, SWE-style tickets and long-horizon agent loops DeepSeek-V4-Pro needs fewer correction turns; Gemini 3.8 Flash is still competent for scripts and assisted completion but trails as task complexity rises.
Multimodal
Gemini 3.8 Flash leads multimodal 88 vs 77. A concrete modality difference: Gemini 3.8 Flash additionally handles audio, image, video.
Speed & latency
Gemini 3.8 Flash is faster in interactive use: ~85 tok/s with 0.3s TTFT versus ~70 tok/s with 0.5s TTFT (about 1.2× the throughput). For conversational UIs where perceived responsiveness drives retention, that edge is a real product factor even when raw reasoning is lower.
Context: window vs usable recall
Nominal windows are 1M for DeepSeek-V4-Pro and 1M for Gemini 3.8 Flash. Effective-context scores point the same way as window size — DeepSeek-V4-Pro is ahead on usable recall (94 vs 90), so prefer it for long-document work where details cannot be missed.
Price & total cost
DeepSeek-V4-Pro is the cheaper API at $0.44/$1.32 versus Gemini 3.8 Flash at $0.75/$3.75 per 1M input/output tokens — list input is about 1.7× lower.
Chinese vs English
English: DeepSeek-V4-Pro 82 vs Gemini 3.8 Flash 88. Chinese: 85 vs 74. For Chinese-language production, DeepSeek-V4-Pro is the stronger pick. Note that non-Chinese models generally require overseas network access for their APIs.
Tool use & ecosystem
Function-calling score: DeepSeek-V4-Pro 82 vs Gemini 3.8 Flash 78, so DeepSeek-V4-Pro has the edge on structured tool use. Fine-tuning is available from DeepSeek-V4-Pro and Gemini 3.8 Flash. Factor in existing SDK/plugin familiarity — switching cost often outweighs a few-point tool-use gap.
Cost worked example — same workload, real token math
Assume a production workload of 100M input + 30M output tokens per month, with 90% of input tokens served from cache. Figures use public list prices.
| Scenario · per month | DeepSeek-V4-Pro | Gemini 3.8 Flash | Gap |
|---|---|---|---|
| List priceno cache applied | $84100M in × $0.44 + 30M out × $1.32 | $188100M in × $0.75 + 30M out × $3.75 | 2.24×gap |
| With caching90% of inputs cache-hit | $84no published cache discount | $188no published cache discount | 2.24×gap |
Illustrative model; your input/output mix and cache-hit ratio change the result. Prices are list rates before any enterprise agreement.