Compare / Gemma 4 26B A4B vs Llama 3.2 3B Instruct
Gemma 4 26B A4B vs Llama 3.2 3B Instruct
Which is cheaper, which is more capable, and which does better at each kind of work, from 15 results on 3 sources that measured both models.
Gemma 4 26B A4B or Llama 3.2 3B Instruct? The short answer
- Llama 3.2 3B Instruct is cheaper: $0.12 against $0.15 per million tokens, 20% less.
- Gemma 4 26B A4B scores higher on the Artificial Analysis Intelligence Index: 16.7 against 5.7.
- On our business benchmarks, Gemma 4 26B A4B ranks higher for agents and tool use, reasoning and knowledge and writing.
At a glance
| Gemma 4 26B A4B | Llama 3.2 3B Instruct | |
|---|---|---|
| Price per million tokens | $0.10 in · $0.30 out | $0.050 in · $0.33 out |
| Blended (3 in : 1 out) | $0.15 | $0.12 |
| Cheapest host, blended | $0.086 (Darkbloom) | $0.12 (Parasail, BF16) |
| Intelligence Index | 16.7 | 5.7 |
| Spring Prompt overall | – | – |
| Output speed, tokens a second | 99 | – |
| Context window | 262,144 tokens | 131,072 tokens |
| Weights | Open | Open |
| Developer based in | the US | the US |
Prices are the developer's list price where we have read it, otherwise the typical host on OpenRouter; see every model's price. Intelligence and speed from Artificial Analysis.
Which is better for what
Each model's rank among models available today, for each kind of work, from our own benchmarks and licensed sources. The better rank is in green.
| Use case | Gemma 4 26B A4B | Llama 3.2 3B Instruct |
|---|---|---|
| Agents and tool useMulti-step tasks with tools: support desks, coding agents, function calls | 90 of 161 | 158 of 161 |
| Reasoning and knowledgeHard questions across science, maths and general knowledge | 100 of 195 | 183 of 195 |
| WritingWhat people prefer in blind comparisons, and judged writing quality | 81 of 187 | 187 of 187 |
| Sticking to the factsSummarising without inventing things, and factual answers | 42 of 153 | not measured |
Every shared result
| Benchmark | Metric | Gemma 4 26B A4B | Llama 3.2 3B Instruct |
|---|---|---|---|
| Arena (formerly LMArena)reported | Business, management and financeArena rating | 1,444 | 1,146 |
| Arena (formerly LMArena)reported | Creative writingArena rating | 1,399 | 1,145 |
| Arena (formerly LMArena)reported | Expert promptsArena rating | 1,475 | 1,179 |
| Arena (formerly LMArena)reported | Instruction followingArena rating | 1,437 | 1,146 |
| Arena (formerly LMArena)reported | OverallArena rating | 1,438 | 1,167 |
| Arena (formerly LMArena)reported | Writing, literature and languageArena rating | 1,406 | 1,143 |
| Artificial Analysisreported | Artificial Analysis Intelligence Indexindex score | 16.7 | 5.70 |
| Artificial Analysisreported | GPQA Diamond% of questions | 79.2% | 25.5% |
| Artificial Analysisreported | Humanity's Last Exam% of questions | 19.3% | 5.3% |
| Artificial Analysisreported | IFBench% of instructions | 72.4% | 26.2% |
| Artificial Analysisreported | Long-context reasoning (AA-LCR)% of questions | 65.7% | 4.3% |
| Artificial Analysisreported | Τ²-bench telecom% of tasks | 43.6% | 21.1% |
| UGI Leaderboardreported | Requested-length error% off the requested word count | 8.0% | 31.0% |
| UGI Leaderboardreported | Style adherencescore from 0 to 1 | 0.35 | 0.36 |
| UGI Leaderboardreported | Writing scorescore out of 100 | 43.8 | 10.4 |
Bold green marks the better value on that metric. Where a source reports ranges that overlap, the difference may not be meaningful; see the benchmark page for ranges.
Quick answers
Is Gemma 4 26B A4B better than Llama 3.2 3B Instruct?
It depends on the task. Among models available today, on our benchmarks and licensed sources, Gemma 4 26B A4B ranks higher for agents and tool use, reasoning and knowledge and writing.
Which is cheaper, Gemma 4 26B A4B or Llama 3.2 3B Instruct?
Llama 3.2 3B Instruct costs $0.12 per million tokens (three input to one output), against $0.15 for Gemma 4 26B A4B.
Run Gemma 4 26B A4B and Llama 3.2 3B Instruct on your own prompt
Benchmarks aren't your data. Try both side by side in the playground, with the cost of every answer.