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

Gemini 3.5 Flash vs DeepSeek-V4-Flash

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

VendorGoogle / DeepSeek
Data fields15+ dimensions
Updated2026-09-08
Read~9 min
01

Verdict at a glance

Bottom line: Choose Gemini 3.5 Flash when its stronger dimensions matter most; choose DeepSeek-V4-Flash when lower cost, lower latency is the priority.

Choose Gemini 3.5 Flash if you…

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

Choose DeepSeek-V4-Flash if you…

  • Rock-bottom price
  • Fast
  • Open source
  • Fit for simple tasks
  • Best for: Ultra-fast response, Low cost, High concurrency
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.

Gemini 3.5 Flash Higher overall
Google · #14 overall
Overall69
Coding64
Multimodal86
VS
DeepSeek-V4-Flash
DeepSeek · #16 overall
Overall67
Coding65
Multimodal65

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.

DimensionGemini 3.5 FlashDeepSeek-V4-FlashVerdict
VendorGoogle (US)DeepSeek (CN)Different vendors
Released2026.072026.04Gemini 3.5 Flash is newer
Overall (rank)69 · #1467 · #16Gemini 3.5 Flash +2
Coding64 · #1765 · #16DeepSeek-V4-Flash +1
Multimodal86 · #765 · #20Gemini 3.5 Flash +21
Context window1M1MTie
Max output128K128KTie
Effective-context8890DeepSeek-V4-Flash more reliable
Input $/1M$1.5$0.14DeepSeek-V4-Flash cheaper
Output $/1M$9$0.28DeepSeek-V4-Flash cheaper
Cache discountnonenoneTie
Speed~80 tok/s~85 tok/sDeepSeek-V4-Flash faster
TTFT0.3s0.3sTie
Function calling7572Gemini 3.5 Flash ahead
Refusal rate~10%~5%DeepSeek-V4-Flash less restrictive
English8575Gemini 3.5 Flash
Chinese7280DeepSeek-V4-Flash
Modalitiestext, image, audio, videotextdifferent coverage
Open weightsNoYesDeepSeek-V4-Flash is open
Fine-tuningYesYes
Free tierGemini App free; API free tierDeepSeek App free
SOC2 / no-trainyes / yesno / yes
Private deploymentNoYesDeepSeek-V4-Flash

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

Gemini 3.5 Flash leads the overall aggregate by 2 points (69 vs 67). That is a meaningful, not marginal, edge on hard, multi-step reasoning, while DeepSeek-V4-Flash remains a strong generalist that is not out of its depth on routine work.

Agentic coding

This is a modest gap: DeepSeek-V4-Flash scores 65 against 64. On multi-file edits, SWE-style tickets and long-horizon agent loops DeepSeek-V4-Flash 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 65. A concrete modality difference: Gemini 3.5 Flash additionally handles audio, image, video.

Speed & latency

DeepSeek-V4-Flash is faster in interactive use: ~85 tok/s with 0.3s TTFT versus ~80 tok/s with 0.3s 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 Gemini 3.5 Flash and 1M for DeepSeek-V4-Flash. Crucially, the larger nominal window does not win on usable recall: Gemini 3.5 Flash advertises 1M but DeepSeek-V4-Flash scores higher on effective-context (90 vs 88), i.e. it actually retains more of what it was given.

Price & total cost

DeepSeek-V4-Flash is the cheaper API at $0.14/$0.28 versus Gemini 3.5 Flash at $1.5/$9 per 1M input/output tokens — list input is about 10.7× lower.

Chinese vs English

English: Gemini 3.5 Flash 85 vs DeepSeek-V4-Flash 75. Chinese: 72 vs 80. For Chinese-language production, DeepSeek-V4-Flash is the stronger pick. Note that non-Chinese models generally require overseas network access for their APIs.

Tool use & ecosystem

Function-calling score: Gemini 3.5 Flash 75 vs DeepSeek-V4-Flash 72, so Gemini 3.5 Flash has the edge on structured tool use. Fine-tuning is available from Gemini 3.5 Flash and DeepSeek-V4-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 monthGemini 3.5 FlashDeepSeek-V4-FlashGap
List priceno cache applied$420100M in × $1.5  +  30M out × $9$22100M in × $0.14  +  30M out × $0.2819.09×gap
With caching90% of inputs cache-hit$420no published cache discount$22no published cache discount19.09×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-Flash (coding 65 vs 64).
IF you serve real-time users and latency is a product KPI  →  choose DeepSeek-V4-Flash (~85 tok/s, 0.3s TTFT).
IF you are cost-driven at scale on routine, high-volume workloads  →  choose DeepSeek-V4-Flash ($$0.14/$$0.28 per 1M in/out).
IF long-document recall has to be near-perfect  →  choose DeepSeek-V4-Flash (effective context 90 vs 88).
07

Frequently asked questions

Is Gemini 3.5 Flash worth the higher price over DeepSeek-V4-Flash?
At list the input rate is 10.7x 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-Flash is the economical pick.
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-Flash. 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, Gemini 3.5 Flash is about $420/month and DeepSeek-V4-Flash about $22/month after cache discounts ($420 and $22 at list).
Does the bigger context window actually matter?
Nominal windows are Gemini 3.5 Flash (1M) and DeepSeek-V4-Flash (1M), but usable recall follows the effective-context score (88 vs 90). 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-Flash is the Chinese model (Chinese score 80, 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.
Can I self-host either model?
DeepSeek-V4-Flash ships open weights and can be self-hosted (GPU permitting) for data control; Gemini 3.5 Flash is a closed managed API with no self-hosting. Choose open weights when residency or cost-at-scale dominates, managed API for convenience.