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DeepSeek V3.1 vs Gemini 2.5 Pro Preview 06-05

DeepSeek V3.1 costs 6.7x less per output token than Gemini 2.5 Pro Preview 06-05 ($1.50 vs $10.00 per million). Updated October 21, 2026; no benchmark has tested both models yet.

DeepSeek V3.1DeepSeek
Coding
No data
Overall
No data
Output $/M
$1.50
Gemini 2.5 Pro Preview 06-05Google
Coding
No data
Overall
No data
Output $/M
$10.00
vs $1.50 vs $10.00 per 1M output tokens. DeepSeek V3.1 is 6.7x cheaper.

DeepSeek V3.1 or Gemini 2.5 Pro Preview 06-05: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick DeepSeek V3.1 for output tokens 6.7x cheaper ($1.50 vs $10.00 per million).

No benchmark has tested both yet. DeepSeek V3.1 has results on AA Intelligence Index, Kagi LLM Benchmark and Design Arena: websites; Gemini 2.5 Pro Preview 06-05 on Aider polyglot, LiveCodeBench (Vals AI) and LiveCodeBench (Artificial Analysis run). Compare them on price and context instead.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
DeepSeek V3.1 not benchmarked, Gemini 2.5 Pro Preview 06-05 not benchmarked.
Widest category
None yet: no category has been tested on both models.
Widest single gap
None yet: no benchmark has tested both models.
Output price
DeepSeek V3.1 $1.50 against Gemini 2.5 Pro Preview 06-05 $10.00 per million output tokens, 6.7x apart.
Context window
DeepSeek V3.1 takes 164K tokens, Gemini 2.5 Pro Preview 06-05 1.05M.

Benchmark by benchmark

Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.

CodingDirectional onlySix of these boards feed the Vibe Coding Index5 boards measured
Coding benchmarks for DeepSeek V3.1 and Gemini 2.5 Pro Preview 06-05
BenchmarkDeepSeek V3.1Gemini 2.5 Pro Preview 06-05Leader
Aider polyglotNot measured83.1%Only Gemini 2.5 Pro Preview 06-05 measured
LiveCodeBench (Vals AI)Not measured79.2%Only Gemini 2.5 Pro Preview 06-05 measured
LiveCodeBench (Artificial Analysis run)Not measured77.8%Only Gemini 2.5 Pro Preview 06-05 measured
GSO-BenchNot measured3.9%Only Gemini 2.5 Pro Preview 06-05 measured
SciCodeNot measured7.7%Only Gemini 2.5 Pro Preview 06-05 measured
Neither model has a result on the other 34 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Intelligence benchmarks for DeepSeek V3.1 and Gemini 2.5 Pro Preview 06-05
BenchmarkDeepSeek V3.1Gemini 2.5 Pro Preview 06-05Leader
AA Intelligence Index13.7Not measuredOnly DeepSeek V3.1 measured
Neither model has a result on the other 1 board here
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
Agentic work benchmarks for DeepSeek V3.1 and Gemini 2.5 Pro Preview 06-05
BenchmarkDeepSeek V3.1Gemini 2.5 Pro Preview 06-05Leader
METR time horizonsNot measured55.4%Only Gemini 2.5 Pro Preview 06-05 measured
Remote Labor IndexNot measured0.8%Only Gemini 2.5 Pro Preview 06-05 measured
DeepResearch BenchNot measured42.8%Only Gemini 2.5 Pro Preview 06-05 measured
Neither model has a result on the other 38 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
Reasoning benchmarks for DeepSeek V3.1 and Gemini 2.5 Pro Preview 06-05
BenchmarkDeepSeek V3.1Gemini 2.5 Pro Preview 06-05Leader
GPQA Diamond (Artificial Analysis run)Not measured83.6%Only Gemini 2.5 Pro Preview 06-05 measured
Humanity's Last Exam (Artificial Analysis run)Not measured19.9%Only Gemini 2.5 Pro Preview 06-05 measured
GPQA Diamond (Epoch AI run)Not measured84.8%Only Gemini 2.5 Pro Preview 06-05 measured
SimpleBenchNot measured62.4%Only Gemini 2.5 Pro Preview 06-05 measured
VPCTNot measured46.4%Only Gemini 2.5 Pro Preview 06-05 measured
Kagi LLM Benchmark53.2%Not measuredOnly DeepSeek V3.1 measured
Neither model has a result on the other 16 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Knowledge benchmarks for DeepSeek V3.1 and Gemini 2.5 Pro Preview 06-05
BenchmarkDeepSeek V3.1Gemini 2.5 Pro Preview 06-05Leader
MMLU Pro (Artificial Analysis run)Not measured85.8%Only Gemini 2.5 Pro Preview 06-05 measured
Neither model has a result on the other 17 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards measured
Web design benchmarks for DeepSeek V3.1 and Gemini 2.5 Pro Preview 06-05
BenchmarkDeepSeek V3.1Gemini 2.5 Pro Preview 06-05Leader
Design Arena: websites1123Not measuredOnly DeepSeek V3.1 measured
Design Arena: UI components1085Not measuredOnly DeepSeek V3.1 measured
Design Arena: game dev1084Not measuredOnly DeepSeek V3.1 measured
Design Arena: data viz1095Not measuredOnly DeepSeek V3.1 measured
Design Arena: 3D1077Not measuredOnly DeepSeek V3.1 measured
Design Arena: all code categories1112Not measuredOnly DeepSeek V3.1 measured
Design Arena: SVG967Not measuredOnly DeepSeek V3.1 measured
Neither model has a result on the other 2 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
General benchmarks for DeepSeek V3.1 and Gemini 2.5 Pro Preview 06-05
BenchmarkDeepSeek V3.1Gemini 2.5 Pro Preview 06-05Leader
DTBench82.7%Not measuredOnly DeepSeek V3.1 measured
LMCA24.3%Not measuredOnly DeepSeek V3.1 measured
Fiction.LiveBenchNot measured91.7%Only Gemini 2.5 Pro Preview 06-05 measured
Neither model has a result on the other 43 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

DeepSeek V3.1$0.0013Fits in one request
Gemini 2.5 Pro Preview 06-05$0.0063Fits in one request

DeepSeek V3.1 costs less

Repository review

50K input + 3K output tokens

DeepSeek V3.1$0.032Fits in one request
Gemini 2.5 Pro Preview 06-05$0.092Fits in one request

DeepSeek V3.1 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V3.1$0.125Exceeds the context window
Gemini 2.5 Pro Preview 06-05$0.350Fits in one request

DeepSeek V3.1 costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of DeepSeek V3.1 and Gemini 2.5 Pro Preview 06-05
SpecificationDeepSeek V3.1Google Gemini 2.5 Pro Preview 06-05
MakerDeepSeekGoogle
WeightsOpen weightsNo public weights listed
ReleasedAugust 21, 2025June 5, 2025
Context window164K1.05M
Input $/Mtok$0.55$1.25
Output $/Mtok$1.50$10.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V3.1 better than Gemini 2.5 Pro Preview 06-05 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick DeepSeek V3.1 for output tokens 6.7x cheaper ($1.50 vs $10.00 per million).

Which is cheaper, DeepSeek V3.1 or Gemini 2.5 Pro Preview 06-05?

DeepSeek V3.1 costs $0.55 per million input tokens and $1.50 per million output tokens; Gemini 2.5 Pro Preview 06-05 costs $1.25 and $10.00. Cost per solved task is known for neither of them.

Which has the bigger context window, DeepSeek V3.1 or Gemini 2.5 Pro Preview 06-05?

Gemini 2.5 Pro Preview 06-05, with 1.05M tokens against 164K.

Has any benchmark tested both DeepSeek V3.1 and Gemini 2.5 Pro Preview 06-05?

No benchmark has tested both yet. DeepSeek V3.1 has results on AA Intelligence Index, Kagi LLM Benchmark and Design Arena: websites; Gemini 2.5 Pro Preview 06-05 on Aider polyglot, LiveCodeBench (Vals AI) and LiveCodeBench (Artificial Analysis run). Compare them on price and context instead. Data as of October 21, 2026.

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