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AI Choice Engine

Model comparison

DeepSeek V3.1 vs Gemini 3.5 Flash-Lite

DeepSeek against Google, compared on context, price, and attributed benchmark results.

Recorded profile verification October 1, 2026Individual provider fields may changeEvidence confidence: Insufficient data — see receipts below

DeepSeek

DeepSeek V3.1

Budget · Open weights

vs

Google

Gemini 3.5 Flash-Lite

Budget

AI model capability comparison
SpecificationDeepSeek V3.1Gemini 3.5 Flash-Lite
ProviderDeepSeekGoogle
TierBudgetBudget
Context window128KWinner: 1.05M
Max outputNot verifiedUnverified66K
Input / 1M tokensNot verifiedUnverified$0.30
Output / 1M tokensNot verifiedUnverified$2.50
WeightsOpenClosed
Parameters671B total / 37B active (MoE)Not verifiedUnverified
Reasoning levelsNot verifiedUnverifiedminimal, low, medium, high
Modalitiestexttext, image, video, audio, pdf
LicenseMITNot verifiedUnverified
API model idNot verifiedUnverifiedgemini-3.5-flash-lite
ReleasedAugust 21, 2025July 21, 2026
Artificial Analysis Intelligence Index · source date Gemini 3.5 Flash-Lite: 2026-10-01Not verifiedUnverified22

Dates beside benchmark scores refer to the linked source’s publication or capture date unless that source explicitly states when it measured the result. A shared URL alone does not establish comparable runs; unverified setups are marked. Prices are USD per million tokens at standard rates, excluding batch and caching discounts. Values we could not confirm from the provider are shown as “Not verified” rather than estimated.

Benchmark receipts

Where each score comes from, and how far it can be compared across models.

  • Source date2026-10-01
    Artificial Analysis (Gemini 3.5 Flash-Lite)

    Composite index blending reasoning, knowledge, and coding evals into one 0–100 score.

    Comparable with caveatOnly same-version scores are comparable. v4.3.2 was rebaselined (the top score fell from 66 on v4.1.1 to ~58), so v4.1.1 figures must not be compared with v4.3.2 figures — check the cited source and its date.

Pricing tiers

DeepSeek V3.1: No current first-party API or verified third-party tariff. deepseek-chat moved to V3.1-Terminus on September 22, 2025; that alias later retired July 24, 2026. MIT weights remain for self-hosting or separately priced hosts. The original checkpoint's hard output cap and selectable hosted effort menu remain unverified.

Gemini 3.5 Flash-Lite: Standard $0.30 input for text/image/video/audio and $2.50 output including thinking per MTok. Cached input $0.03 plus $1/MTok-hour storage. Batch/Flex $0.15/$1.25 with published cached input $0.02. Priority $0.54/$4.50, cached $0.05. Grounding tools have separate charges/quotas. The older 3.1 Flash-Lite has modality-dependent input rates.

BudgetOpen weightsRecord checked October 1, 2026

DeepSeek V3.1

DeepSeek V3.1 is a legacy open-weight (MIT) 671B/37B MoE with a 128K context — superseded by V3.1-Terminus, V3.2 and then V4.

Best for

  • Cost-sensitive hosted agents
  • High-volume coding assist
  • Open-weight deployments

Watch out

Legacy: DeepSeek's first-party alias moved to V3.1-Terminus on September 22, 2025. Pin the exact V3.1 checkpoint; current hosted rates depend on provider. The original card supports thinking/non-thinking templates, not a verified selectable low/high/max menu. Self-hosting memory depends on quantization, offloading and hardware.

BudgetRecord checked October 1, 2026

Gemini 3.5 Flash-Lite

Gemini 3.5 Flash-Lite is Google's recommended Flash-Lite tier for high-volume, latency-sensitive agent loops.

Best for

  • High-volume agents
  • Document pipelines
  • Cost-sensitive multimodal

Watch out

Compare input modality: 3.1 Flash-Lite is $0.25 for text/image/video but $0.50 for audio, versus this model's $0.30 for either. Thinking includes minimal through high; computer use is Preview. Price alone does not establish quality on reasoning tasks.

When the cheaper one wins

One of these rows is missing a verified output price, so this page will not name a cheaper winner. Run the model picker against the actual job instead of guessing.

Run the model picker

Evidence confidence: Insufficient data

How strong and complete the evidence behind this comparison is — not a prediction of which model is better. Hard limitations apply: missing pricing; evidence too sparse.

  • Pricing incomplete — No verified token pricing for DeepSeek V3.1.
  • 2/5 core specs verified on both sides — Not published for at least one side: max output, parameter count, reasoning levels.
  • No directly aligned benchmark setup — No benchmark has matching cited sources, source dates, units, effort and recorded run details on both models.
  • Verified within the last 90 days — Older of the two catalog checks was 25 days ago.
  • Both models carry source citations — Each side has at least two catalog sources on record.

Source receipts

Each catalog figure was checked against the provider or an independent second source on the date shown.

Related comparisons

Diving deeper on one model? DeepSeek V3.1 · Gemini 3.5 Flash-Lite

Common questions

DeepSeek V3.1 vs Gemini 3.5 Flash-Lite

Answered from the verified figures on this page rather than general guidance.

Which has the larger context window, DeepSeek V3.1 or Gemini 3.5 Flash-Lite?
Gemini 3.5 Flash-Lite accepts 1.05M tokens against 128K for DeepSeek V3.1. This only matters if you routinely send very long documents or large codebases.
Should I use DeepSeek V3.1 or Gemini 3.5 Flash-Lite?
Both are classified in our budget tier; this editorial grouping does not imply equal capability. DeepSeek V3.1 is a candidate for cost-sensitive hosted agents; Gemini 3.5 Flash-Lite is a candidate for high-volume agents. Compare accuracy, tool reliability, latency and cost on representative tasks.
Can I self-host DeepSeek V3.1 or Gemini 3.5 Flash-Lite?
DeepSeek V3.1 publishes open weights, but self-hosting and third-party provider access depend on the licence, hardware, serving support, and availability. Gemini 3.5 Flash-Lite is a closed model whose supported access paths are controlled by its provider.

Next step

Choosing between them

The verified figures that separate this pair, computed from the catalog rather than restated boilerplate.

  • Context: Gemini 3.5 Flash-Lite takes 1.05M against 128K for DeepSeek V3.1 — only decisive if your prompts approach the smaller window.
  • Deployment: DeepSeek V3.1 publishes weights you can self-host; the other is API-only.
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