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DeepSeek V3.1 Terminus vs Gemma 2 27B

Gemma 2 27B costs 1.6x less per output token than DeepSeek V3.1 Terminus ($0.65 vs $1.0142 per million). Updated October 21, 2026; 22 benchmarks have a result for both.

DeepSeek V3.1 TerminusDeepSeek
Coding
No data
Overall
No data
Output $/M
$1.0142
22
Gemma 2 27BGoogle
Coding
No data
Overall
No data
Output $/M
$0.65
0
vs boards won of 22 shared

DeepSeek V3.1 Terminus or Gemma 2 27B: which to pick

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

Pick DeepSeek V3.1 Terminus for a larger context window (164K against 8K tokens).

Shared results
22
DeepSeek V3.1 Terminus only
23
Gemma 2 27B only
14
Like-for-like categories
5 of 9

Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.

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 Terminus not benchmarked, Gemma 2 27B not benchmarked.
Widest category
Knowledge, 38.2 points apart on average over 4 shared benchmarks.
Widest single gap
LMArena Text: medicine and healthcare: DeepSeek V3.1 Terminus 1468 against Gemma 2 27B 1198, 45.1 points apart on a 0 to 100 scale.
Output price
DeepSeek V3.1 Terminus $1.0142 against Gemma 2 27B $0.65 per million output tokens, 1.6x apart.
Context window
DeepSeek V3.1 Terminus takes 164K tokens, Gemma 2 27B 8K.

Benchmark by benchmark

First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.

Boards won, where both have a result
CategoryDeepSeek V3.1 TerminusBarsGemma 2 27BTies
Coding20
Reasoning20
Math10
Knowledge40
General130
All shared boards220
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
Coding benchmarks for DeepSeek V3.1 Terminus and Gemma 2 27B
BenchmarkDeepSeek V3.1 TerminusGemma 2 27BLeader
AA Coding Index43.5Not measuredOnly DeepSeek V3.1 Terminus measured
LiveCodeBench (Artificial Analysis run)79.8%Not measuredOnly DeepSeek V3.1 Terminus measured
SciCode38.0%Not measuredOnly DeepSeek V3.1 Terminus measured
Terminal-Bench Hard (Artificial Analysis run)31.8%Not measuredOnly DeepSeek V3.1 Terminus measured
ALE-Bench745.2Not measuredOnly DeepSeek V3.1 Terminus measured
LMArena Text: coding14251211DeepSeek V3.1 Terminus
LMArena Text: software and IT14261228DeepSeek V3.1 Terminus
Neither model has a result on the other 32 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Intelligence benchmarks for DeepSeek V3.1 Terminus and Gemma 2 27B
BenchmarkDeepSeek V3.1 TerminusGemma 2 27BLeader
AA Intelligence Index14.8Not measuredOnly DeepSeek V3.1 Terminus measured
Epoch Capabilities IndexNot measured122.1Only Gemma 2 27B measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Agentic work benchmarks for DeepSeek V3.1 Terminus and Gemma 2 27B
BenchmarkDeepSeek V3.1 TerminusGemma 2 27BLeader
AA Agentic Index6.8Not measuredOnly DeepSeek V3.1 Terminus measured
τ²-Bench Telecom37.1%Not measuredOnly DeepSeek V3.1 Terminus measured
Neither model has a result on the other 39 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
Reasoning benchmarks for DeepSeek V3.1 Terminus and Gemma 2 27B
BenchmarkDeepSeek V3.1 TerminusGemma 2 27BLeader
GPQA Diamond (Artificial Analysis run)79.2%Not measuredOnly DeepSeek V3.1 Terminus measured
Humanity's Last Exam (Artificial Analysis run)16.4%Not measuredOnly DeepSeek V3.1 Terminus measured
GPQA Diamond (Epoch AI run)Not measured36.5%Only Gemma 2 27B measured
LMArena Text: hard prompts14261198DeepSeek V3.1 Terminus
LMArena Text: expertNot measured1171Only Gemma 2 27B measured
LMArena Text: hard prompts in English14321206DeepSeek V3.1 Terminus
Kagi LLM Benchmark57.4%Not measuredOnly DeepSeek V3.1 Terminus measured
Neither model has a result on the other 15 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index10
Math benchmarks for DeepSeek V3.1 Terminus and Gemma 2 27B
BenchmarkDeepSeek V3.1 TerminusGemma 2 27BLeader
AA Math Index89.7Not measuredOnly DeepSeek V3.1 Terminus measured
AIME 2025 (Artificial Analysis run)89.7%Not measuredOnly DeepSeek V3.1 Terminus measured
OTIS Mock AIMENot measured1.4%Only Gemma 2 27B measured
MATH level 5Not measured27.9%Only Gemma 2 27B measured
LMArena Text: math14021212DeepSeek V3.1 Terminus
LMArena Text: mathematical workNot measured1221Only Gemma 2 27B measured
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for DeepSeek V3.1 Terminus and Gemma 2 27B
BenchmarkDeepSeek V3.1 TerminusGemma 2 27BLeader
LegalBench (Vals AI)Not measured68.0%Only Gemma 2 27B measured
MMLU Pro (Artificial Analysis run)85.1%Not measuredOnly DeepSeek V3.1 Terminus measured
MMLUNot measured75.7%Only Gemma 2 27B measured
LMArena Text: science14511228DeepSeek V3.1 Terminus
LMArena Text: medicine and healthcare14681198DeepSeek V3.1 Terminus
LMArena Text: legal and government14571241DeepSeek V3.1 Terminus
LMArena Text: business and finance14141208DeepSeek V3.1 Terminus
Neither model has a result on the other 11 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Web design benchmarks for DeepSeek V3.1 Terminus and Gemma 2 27B
BenchmarkDeepSeek V3.1 TerminusGemma 2 27BLeader
Design Arena: websites1187Not measuredOnly DeepSeek V3.1 Terminus measured
Design Arena: UI components1182Not measuredOnly DeepSeek V3.1 Terminus measured
Design Arena: game dev1131Not measuredOnly DeepSeek V3.1 Terminus measured
Design Arena: data viz1167Not measuredOnly DeepSeek V3.1 Terminus measured
Design Arena: 3D1141Not measuredOnly DeepSeek V3.1 Terminus measured
Design Arena: all code categories1175Not measuredOnly DeepSeek V3.1 Terminus measured
Design Arena: SVG1065Not measuredOnly DeepSeek V3.1 Terminus measured
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index130
General benchmarks for DeepSeek V3.1 Terminus and Gemma 2 27B
BenchmarkDeepSeek V3.1 TerminusGemma 2 27BLeader
IFBench57.0%Not measuredOnly DeepSeek V3.1 Terminus measured
Long context reasoning (AA-LCR)69.3%Not measuredOnly DeepSeek V3.1 Terminus measured
DTBench81.3%48.0%DeepSeek V3.1 Terminus
LMCA28.6%7.1%DeepSeek V3.1 Terminus
LMArena Text14191231DeepSeek V3.1 Terminus
LMArena Text: instruction following14041206DeepSeek V3.1 Terminus
LMArena Text: creative writing14031240DeepSeek V3.1 Terminus
LMArena Text: English14291242DeepSeek V3.1 Terminus
LMArena Text: non-English14081217DeepSeek V3.1 Terminus
LMArena Text: ChineseNot measured1221Only Gemma 2 27B measured
LMArena Text: GermanNot measured1209Only Gemma 2 27B measured
LMArena Text: JapaneseNot measured1175Only Gemma 2 27B measured
LMArena Text: KoreanNot measured1174Only Gemma 2 27B measured
LMArena Text: FrenchNot measured1248Only Gemma 2 27B measured
LMArena Text: SpanishNot measured1228Only Gemma 2 27B measured
LMArena Text: Russian14351234DeepSeek V3.1 Terminus
LMArena Text: Polish14271277DeepSeek V3.1 Terminus
LMArena Text: multi-turn14111224DeepSeek V3.1 Terminus
LMArena Text: longer queries14221230DeepSeek V3.1 Terminus
LMArena Text: writing and language14091249DeepSeek V3.1 Terminus
LMArena Text: entertainment and media13911212DeepSeek V3.1 Terminus
Neither model has a result on the other 25 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for DeepSeek V3.1 Terminus and Gemma 2 27B
BenchmarkDeepSeek V3.1 TerminusGemma 2 27BLeader
Neither model has a result on 5 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 Terminus$0.0008Fits in one request
Gemma 2 27B$0.0010Fits in one request

DeepSeek V3.1 Terminus costs less

Repository review

50K input + 3K output tokens

DeepSeek V3.1 Terminus$0.018Fits in one request
Gemma 2 27B$0.034Exceeds the context window

DeepSeek V3.1 Terminus costs less

Agent loop

200K input + 10K output tokens

DeepSeek V3.1 Terminus$0.071Exceeds the context window
Gemma 2 27B$0.137Exceeds the context window

DeepSeek V3.1 Terminus 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 Terminus and Gemma 2 27B
SpecificationDeepSeek V3.1 TerminusGoogle Gemma 2 27B
MakerDeepSeekGoogle
WeightsOpen weightsOpen weights
ReleasedSeptember 22, 2025July 13, 2024
Context window164K8K
Input $/Mtok$0.3063$0.65
Output $/Mtok$1.0142$0.65
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V3.1 Terminus better than Gemma 2 27B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick DeepSeek V3.1 Terminus for a larger context window (164K against 8K tokens).

Which is cheaper, DeepSeek V3.1 Terminus or Gemma 2 27B?

DeepSeek V3.1 Terminus costs $0.3063 per million input tokens and $1.0142 per million output tokens; Gemma 2 27B costs $0.65 and $0.65. Cost per solved task is known for neither of them.

Which has the bigger context window, DeepSeek V3.1 Terminus or Gemma 2 27B?

DeepSeek V3.1 Terminus, with 164K tokens against 8K.

How many benchmarks is the DeepSeek V3.1 Terminus vs Gemma 2 27B comparison based on?

22 benchmarks have a result for both models as of October 21, 2026. DeepSeek V3.1 Terminus's coding index rests on 0 independent benchmarks and Gemma 2 27B's on 0. Where only one model has a result, the page says so instead of naming a winner.

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