Command R (08-2024) vs Gemma 3 27B
Gemma 3 27B costs 2.0x less per output token than Command R (08-2024) ($0.30 vs $0.60 per million). Updated October 21, 2026; 25 benchmarks have a result for both.
Command R (08-2024) or Gemma 3 27B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Command R (08-2024) for work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.
- Shared results
- 25
- Command R (08-2024) only
- 0
- Gemma 3 27B only
- 41
- 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.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Gemma 3 27B has a AA Intelligence Index result, 4.9.
Directional only
Agentic work
AA Agentic Index
No call
Only Gemma 3 27B has a AA Agentic Index result, 0.1.
Directional only
Long documents
Listed context window
Gemma 3 27B
Gemma 3 27B takes 131K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemma 3 27B
Command R (08-2024) $0.0004, Gemma 3 27B $0.0002 per turn.
List prices
At a glance
- Coding index
- Command R (08-2024) not benchmarked, Gemma 3 27B not benchmarked.
- Widest category
- Reasoning, 24.7 points apart on average over 3 shared benchmarks.
- Widest single gap
- LMArena Text: hard prompts in English: Command R (08-2024) 1194 against Gemma 3 27B 1353, 26.5 points apart on a 0 to 100 scale.
- Output price
- Command R (08-2024) $0.60 against Gemma 3 27B $0.30 per million output tokens, 2.0x apart.
- Context window
- Command R (08-2024) takes 128K tokens, Gemma 3 27B 131K.
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.
| Category | Command R (08-2024) | Bars | Gemma 3 27B | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Reasoning | 0 | 3 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 4 | ||
| General | 0 | 14 | ||
| All shared boards | 0 | 25 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
| Benchmark | Command R (08-2024) | Gemma 3 27B | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 4.9% | Only Gemma 3 27B measured |
| AA Coding Index | Not measured | 10.1 | Only Gemma 3 27B measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 13.7% | Only Gemma 3 27B measured |
| SciCode | Not measured | 23.3% | Only Gemma 3 27B measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 3.8% | Only Gemma 3 27B measured |
| LMArena Text: coding | 1187 | 1322 | Gemma 3 27B |
| LMArena Text: software and IT | 1197 | 1354 | Gemma 3 27B |
| SciCode | Not measured | 0.0% | Only Gemma 3 27B measured |
| Neither model has a result on the other 31 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Command R (08-2024) | Gemma 3 27B | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 4.9 | Only Gemma 3 27B measured |
| Epoch Capabilities Index | Not measured | 130.0 | Only Gemma 3 27B measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Command R (08-2024) | Gemma 3 27B | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 0.1 | Only Gemma 3 27B measured |
| τ²-Bench Telecom | Not measured | 10.5% | Only Gemma 3 27B measured |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 29.5% | Only Gemma 3 27B measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Command R (08-2024) | Gemma 3 27B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 42.8% | Only Gemma 3 27B measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 4.4% | Only Gemma 3 27B measured |
| GPQA Diamond (Epoch AI run) | Not measured | 47.7% | Only Gemma 3 27B measured |
| LMArena Text: hard prompts | 1186 | 1340 | Gemma 3 27B |
| LMArena Text: expert | 1173 | 1304 | Gemma 3 27B |
| LMArena Text: hard prompts in English | 1194 | 1353 | Gemma 3 27B |
| LMArena Vision: diagrams | Not measured | 1156 | Only Gemma 3 27B measured |
| LMArena Vision: homework | Not measured | 1160 | Only Gemma 3 27B measured |
| Kagi LLM Benchmark | Not measured | 35.1% | Only Gemma 3 27B measured |
| Neither model has a result on the other 13 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Command R (08-2024) | Gemma 3 27B | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 20.7 | Only Gemma 3 27B measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 20.7% | Only Gemma 3 27B measured |
| OTIS Mock AIME | Not measured | 22.5% | Only Gemma 3 27B measured |
| MATH level 5 | Not measured | 74.0% | Only Gemma 3 27B measured |
| LMArena Text: math | 1188 | 1312 | Gemma 3 27B |
| LMArena Text: mathematical work | 1198 | 1327 | Gemma 3 27B |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Command R (08-2024) | Gemma 3 27B | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | Not measured | 66.9% | Only Gemma 3 27B measured |
| GeoBench | Not measured | 52.0% | Only Gemma 3 27B measured |
| LMArena Text: science | 1252 | 1383 | Gemma 3 27B |
| LMArena Text: medicine and healthcare | 1238 | 1391 | Gemma 3 27B |
| LMArena Text: legal and government | 1268 | 1375 | Gemma 3 27B |
| LMArena Text: business and finance | 1215 | 1360 | Gemma 3 27B |
| FACTS Benchmark Suite | Not measured | 29.1% | Only Gemma 3 27B measured |
| Neither model has a result on the other 11 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Command R (08-2024) | Gemma 3 27B | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index014
| Benchmark | Command R (08-2024) | Gemma 3 27B | Leader |
|---|---|---|---|
| IFBench | Not measured | 31.8% | Only Gemma 3 27B measured |
| Long context reasoning (AA-LCR) | Not measured | 7.3% | Only Gemma 3 27B measured |
| DTBench | Not measured | 52.5% | Only Gemma 3 27B measured |
| LMCA | Not measured | 12.3% | Only Gemma 3 27B measured |
| Fiction.LiveBench | Not measured | 33.3% | Only Gemma 3 27B measured |
| Creative writing (Lech Mazur) | Not measured | 79.9% | Only Gemma 3 27B measured |
| LMArena Text | 1229 | 1358 | Gemma 3 27B |
| LMArena Text: instruction following | 1197 | 1321 | Gemma 3 27B |
| LMArena Text: creative writing | 1234 | 1345 | Gemma 3 27B |
| LMArena Vision | Not measured | 1165 | Only Gemma 3 27B measured |
| LMArena Text: English | 1238 | 1377 | Gemma 3 27B |
| LMArena Text: non-English | 1216 | 1334 | Gemma 3 27B |
| LMArena Text: Chinese | 1227 | 1346 | Gemma 3 27B |
| LMArena Text: German | 1216 | 1362 | Gemma 3 27B |
| LMArena Text: Japanese | 1166 | 1287 | Gemma 3 27B |
| LMArena Text: Korean | 1162 | 1308 | Gemma 3 27B |
| LMArena Text: French | Not measured | 1368 | Only Gemma 3 27B measured |
| LMArena Text: Spanish | Not measured | 1349 | Only Gemma 3 27B measured |
| LMArena Text: Russian | 1227 | 1349 | Gemma 3 27B |
| LMArena Text: Polish | Not measured | 1345 | Only Gemma 3 27B measured |
| LMArena Text: multi-turn | 1213 | 1345 | Gemma 3 27B |
| LMArena Text: longer queries | 1230 | 1333 | Gemma 3 27B |
| LMArena Text: writing and language | 1241 | 1347 | Gemma 3 27B |
| LMArena Text: entertainment and media | 1223 | 1320 | Gemma 3 27B |
| LMArena Vision: English | Not measured | 1188 | Only Gemma 3 27B measured |
| LMArena Vision: Chinese | Not measured | 1164 | Only Gemma 3 27B measured |
| LMArena Vision: reading text | Not measured | 1156 | Only Gemma 3 27B measured |
| LMArena Vision: humor | Not measured | 1166 | Only Gemma 3 27B measured |
| LMArena Vision: captioning | Not measured | 1151 | Only Gemma 3 27B measured |
| LMArena Vision: recognizing things | Not measured | 1196 | Only Gemma 3 27B measured |
| LMArena Vision: creative writing | Not measured | 1177 | Only Gemma 3 27B measured |
| Neither model has a result on the other 15 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Command R (08-2024) | Gemma 3 27B | Leader |
|---|---|---|---|
| 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
Gemma 3 27B costs less
Repository review
50K input + 3K output tokens
Gemma 3 27B costs less
Agent loop
200K input + 10K output tokens
Gemma 3 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 | Cohere Command R (08-2024) | Google Gemma 3 27B |
|---|---|---|
| Maker | Cohere | |
| Weights | No public weights listed | Open weights |
| Released | August 30, 2024 | March 12, 2025 |
| Context window | 128K | 131K |
| Input $/Mtok | $0.15 | $0.08 |
| Output $/Mtok | $0.60 | $0.30 |
| 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 Command R (08-2024) better than Gemma 3 27B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Command R (08-2024) for work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.
Which is cheaper, Command R (08-2024) or Gemma 3 27B?
Command R (08-2024) costs $0.15 per million input tokens and $0.60 per million output tokens; Gemma 3 27B costs $0.08 and $0.30. Cost per solved task is known for neither of them.
Which has the bigger context window, Command R (08-2024) or Gemma 3 27B?
Gemma 3 27B, with 131K tokens against 128K.
How many benchmarks is the Command R (08-2024) vs Gemma 3 27B comparison based on?
25 benchmarks have a result for both models as of October 21, 2026. Command R (08-2024)'s coding index rests on 0 independent benchmarks and Gemma 3 27B's on 0. Where only one model has a result, the page says so instead of naming a winner.