MModelspectraIndependent AI Model Intelligence
Head-to-head · Updated 2026-09-08
Model Comparison · Head to Head

DeepSeek-V4-Pro vs Gemini 3.5 Flash

DeepSeek-V4-Pro wins on Overall, Coding; Gemini 3.5 Flash wins on Multimodal. Every numeric field is compared below, with a worked monthly-cost example and a pick rule for each use case.

VendorDeepSeek / Google
Data fields15+ dimensions
Updated2026-09-08
Read~9 min
01

Verdict at a glance

Bottom line: Choose DeepSeek-V4-Pro when coding depth, long-context reliability, lower refusal matter most; choose Gemini 3.5 Flash when lower latency is the priority.

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 3.5 Flash if you…

  • Extremely fast
  • Low price
  • Native multimodal
  • Built for scale
  • Best for: Fast tasks, Multimodal, Low cost
02

Head-to-head aggregate scores

Scores are 0–100, aggregated from public benchmark information and independently weighted across three leaderboards. Rank is out of 22 tracked models.

DeepSeek-V4-Pro Higher overall
DeepSeek · #8 overall
Overall77
Coding79
Multimodal77
VS
Gemini 3.5 Flash
Google · #14 overall
Overall69
Coding64
Multimodal86

Aggregated from public sources and independently weighted; methodology on the Terms page. Scores within 3 points are treated as statistically tied.

03

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.

DimensionDeepSeek-V4-ProGemini 3.5 FlashVerdict
VendorDeepSeek (CN)Google (US)Different vendors
Released2026.042026.07Gemini 3.5 Flash is newer
Overall (rank)77 · #869 · #14DeepSeek-V4-Pro +8
Coding79 · #564 · #17DeepSeek-V4-Pro +15
Multimodal77 · #1386 · #7Gemini 3.5 Flash +9
Context window1M1MTie
Max output128K128KTie
Effective-context9488DeepSeek-V4-Pro more reliable
Input $/1M$0.44$1.5DeepSeek-V4-Pro cheaper
Output $/1M$1.32$9DeepSeek-V4-Pro cheaper
Cache discountnonenoneTie
Speed~70 tok/s~80 tok/sGemini 3.5 Flash faster
TTFT0.5s0.3sGemini 3.5 Flash snappier
Function calling8275DeepSeek-V4-Pro ahead
Refusal rate~5%~10%DeepSeek-V4-Pro less restrictive
English8285Gemini 3.5 Flash
Chinese8572DeepSeek-V4-Pro
Modalitiestexttext, image, audio, videodifferent coverage
Open weightsYesNoDeepSeek-V4-Pro is open
Fine-tuningYesYes
Free tierDeepSeek App free; new API users receive creditsGemini App free; API free tier
SOC2 / no-trainno / yesyes / yes
Private deploymentYesNoDeepSeek-V4-Pro

Fields drawn from vendor public documentation and the Modelspectra 22-model dataset; speed varies with network, concurrency and prompt length. Verify current pricing before purchase.

04

Dimension-by-dimension analysis

Reasoning & overall intelligence

DeepSeek-V4-Pro leads the overall aggregate by 8 points (77 vs 69). That is a meaningful, not marginal, edge on hard, multi-step reasoning, while Gemini 3.5 Flash remains a strong generalist that is not out of its depth on routine work.

Agentic coding

This is a clear gap: DeepSeek-V4-Pro scores 79 against 64. On multi-file edits, SWE-style tickets and long-horizon agent loops DeepSeek-V4-Pro needs fewer correction turns; Gemini 3.5 Flash is still competent for scripts and assisted completion but trails as task complexity rises.

Multimodal

Gemini 3.5 Flash leads multimodal 86 vs 77. A concrete modality difference: Gemini 3.5 Flash additionally handles audio, image, video.

Speed & latency

Gemini 3.5 Flash is faster in interactive use: ~80 tok/s with 0.3s TTFT versus ~70 tok/s with 0.5s TTFT (about 1.1× 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 3.5 Flash. Effective-context scores point the same way as window size — DeepSeek-V4-Pro is ahead on usable recall (94 vs 88), 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 3.5 Flash at $1.5/$9 per 1M input/output tokens — list input is about 3.4× lower.

Chinese vs English

English: DeepSeek-V4-Pro 82 vs Gemini 3.5 Flash 85. Chinese: 85 vs 72. 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 3.5 Flash 75, so DeepSeek-V4-Pro has the edge on structured tool use. Fine-tuning is available from DeepSeek-V4-Pro and Gemini 3.5 Flash. Factor in existing SDK/plugin familiarity — switching cost often outweighs a few-point tool-use gap.

05

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 monthDeepSeek-V4-ProGemini 3.5 FlashGap
List priceno cache applied$84100M in × $0.44  +  30M out × $1.32$420100M in × $1.5  +  30M out × $95.00×gap
With caching90% of inputs cache-hit$84no published cache discount$420no published cache discount5.00×gap

Illustrative model; your input/output mix and cache-hit ratio change the result. Prices are list rates before any enterprise agreement.

06

Decision tree

IF the workload is agentic or multi-file coding and a wrong first pass is expensive  →  choose DeepSeek-V4-Pro (coding 79 vs 64).
IF you serve real-time users and latency is a product KPI  →  choose Gemini 3.5 Flash (~80 tok/s, 0.3s TTFT).
IF you are cost-driven at scale on routine, high-volume workloads  →  choose DeepSeek-V4-Pro ($$0.44/$$1.32 per 1M in/out).
IF long-document recall has to be near-perfect  →  choose DeepSeek-V4-Pro (effective context 94 vs 88).
07

Frequently asked questions

Is Gemini 3.5 Flash worth the higher price over DeepSeek-V4-Pro?
At list the input rate is 3.4x higher, but cache discounts and output pricing narrow the effective gap. Pay the premium when Gemini 3.5 Flash's stronger dimensions protect revenue; for routine volume DeepSeek-V4-Pro is the economical pick.
Which is better for agentic coding?
DeepSeek-V4-Pro is decisively stronger for coding (79 vs 64 on the aggregate). The gap shows on SWE-style multi-file tasks and long agent loops that need fewer correction turns; Gemini 3.5 Flash is fine for routine scripts.
Does Gemini 3.5 Flash's higher refusal rate matter in production?
Gemini 3.5 Flash refuses about 10% of prompts versus 5% for DeepSeek-V4-Pro. In unattended pipelines that means more retries, fallbacks and manual review, raising effective cost and latency even when the token price is lower.
How do costs compare at 100M tokens/month with caching?
At 100M input + 30M output with 90% of inputs cache-hit, DeepSeek-V4-Pro is about $84/month and Gemini 3.5 Flash about $420/month after cache discounts ($84 and $420 at list).
Does the bigger context window actually matter?
Nominal windows are DeepSeek-V4-Pro (1M) and Gemini 3.5 Flash (1M), but usable recall follows the effective-context score (94 vs 88). Prefer the higher effective-context model for long-document work where nothing can be missed.
How do they differ for Chinese-language and data-residency use?
DeepSeek-V4-Pro is the Chinese model (Chinese score 85, domestic cloud, possible private deployment) while Gemini 3.5 Flash is the global model (Chinese 72, overseas API). Pick by language quality, access path and where data must reside.