Gemma 2 27B vs Llama 3.1 Euryale 70B v2.2
Gemma 2 27B costs 1.3x less per output token than Llama 3.1 Euryale 70B v2.2 ($0.65 vs $0.85 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.65
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.85
Gemma 2 27B or Llama 3.1 Euryale 70B v2.2: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Gemma 2 27B for output tokens 1.3x cheaper ($0.65 vs $0.85 per million).
No benchmark has tested both yet. Gemma 2 27B has results on LMArena Text: coding, LMArena Text: software and IT and Epoch Capabilities Index; Llama 3.1 Euryale 70B v2.2 has none yet. 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.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Long documents
Listed context window
Llama 3.1 Euryale 70B v2.2
Llama 3.1 Euryale 70B v2.2 takes 131K tokens against 8K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemma 2 27B
Gemma 2 27B $0.0010, Llama 3.1 Euryale 70B v2.2 $0.0013 per turn.
List prices
At a glance
- Coding index
- Gemma 2 27B not benchmarked, Llama 3.1 Euryale 70B v2.2 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
- Gemma 2 27B $0.65 against Llama 3.1 Euryale 70B v2.2 $0.85 per million output tokens, 1.3x apart.
- Context window
- Gemma 2 27B takes 8K tokens, Llama 3.1 Euryale 70B v2.2 131K.
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 Index2 boards measured
| Benchmark | Gemma 2 27B | Llama 3.1 Euryale 70B v2.2 | Leader |
|---|---|---|---|
| LMArena Text: coding | 1211 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: software and IT | 1228 | Not measured | Only Gemma 2 27B measured |
| Neither model has a result on the other 41 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Gemma 2 27B | Llama 3.1 Euryale 70B v2.2 | Leader |
|---|---|---|---|
| Epoch Capabilities Index | 122.1 | Not measured | Only Gemma 2 27B measured |
| Neither model has a result on the other 1 board here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | Gemma 2 27B | Llama 3.1 Euryale 70B v2.2 | Leader |
|---|---|---|---|
| GPQA Diamond (Epoch AI run) | 36.5% | Not measured | Only Gemma 2 27B measured |
| LMArena Text: hard prompts | 1198 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: expert | 1171 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: hard prompts in English | 1206 | Not measured | Only Gemma 2 27B measured |
| Neither model has a result on the other 19 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | Gemma 2 27B | Llama 3.1 Euryale 70B v2.2 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 1.4% | Not measured | Only Gemma 2 27B measured |
| MATH level 5 | 27.9% | Not measured | Only Gemma 2 27B measured |
| LMArena Text: math | 1212 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: mathematical work | 1221 | Not measured | Only Gemma 2 27B measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
| Benchmark | Gemma 2 27B | Llama 3.1 Euryale 70B v2.2 | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | 68.0% | Not measured | Only Gemma 2 27B measured |
| MMLU | 75.7% | Not measured | Only Gemma 2 27B measured |
| LMArena Text: science | 1228 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: medicine and healthcare | 1198 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: legal and government | 1241 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: business and finance | 1208 | Not measured | Only Gemma 2 27B measured |
| Neither model has a result on the other 14 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index19 boards measured
| Benchmark | Gemma 2 27B | Llama 3.1 Euryale 70B v2.2 | Leader |
|---|---|---|---|
| DTBench | 48.0% | Not measured | Only Gemma 2 27B measured |
| LMCA | 7.1% | Not measured | Only Gemma 2 27B measured |
| LMArena Text | 1231 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: instruction following | 1206 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: creative writing | 1240 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: English | 1242 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: non-English | 1217 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: Chinese | 1221 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: German | 1209 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: Japanese | 1175 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: Korean | 1174 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: French | 1248 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: Spanish | 1228 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: Russian | 1234 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: Polish | 1277 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: multi-turn | 1224 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: longer queries | 1230 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: writing and language | 1249 | Not measured | Only Gemma 2 27B measured |
| LMArena Text: entertainment and media | 1212 | Not measured | Only Gemma 2 27B measured |
| Neither model has a result on the other 29 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
Gemma 2 27B costs less
Repository review
50K input + 3K output tokens
Gemma 2 27B costs less
Agent loop
200K input + 10K output tokens
Gemma 2 27B 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.
| Specification | Google Gemma 2 27B | Sao10K Llama 3.1 Euryale 70B v2.2 |
|---|---|---|
| Maker | Sao10K | |
| Weights | Open weights | Open weights |
| Released | July 13, 2024 | August 28, 2024 |
| Context window | 8K | 131K |
| Input $/Mtok | $0.65 | $0.85 |
| Output $/Mtok | $0.65 | $0.85 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemma 2 27B better than Llama 3.1 Euryale 70B v2.2 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Gemma 2 27B for output tokens 1.3x cheaper ($0.65 vs $0.85 per million).
Which is cheaper, Gemma 2 27B or Llama 3.1 Euryale 70B v2.2?
Gemma 2 27B costs $0.65 per million input tokens and $0.65 per million output tokens; Llama 3.1 Euryale 70B v2.2 costs $0.85 and $0.85. Cost per solved task is known for neither of them.
Which has the bigger context window, Gemma 2 27B or Llama 3.1 Euryale 70B v2.2?
Llama 3.1 Euryale 70B v2.2, with 131K tokens against 8K.
Has any benchmark tested both Gemma 2 27B and Llama 3.1 Euryale 70B v2.2?
No benchmark has tested both yet. Gemma 2 27B has results on LMArena Text: coding, LMArena Text: software and IT and Epoch Capabilities Index; Llama 3.1 Euryale 70B v2.2 has none yet. Compare them on price and context instead. Data as of October 22, 2026.