| Signal | Gemma 2 27B | Delta | Llama 4 Maverick |
|---|---|---|---|
Capabilities | 33 | -33 | |
Benchmarks | 83 | +4 | |
Pricing | 1 | +0 | |
Context window size | 62 | -33 | |
Recency | 18 | -49 | |
Output Capacity | 55 | -15 | |
| Overall Result | 2 wins | of 6 | 4 wins |
9
days higher
3
days
18
days higher
Meta
Llama 4 Maverick saves you $52.50/month
That's $630.00/year compared to Gemma 2 27B at your current usage level of 100K calls/month.
| Metric | Gemma 2 27B | Llama 4 Maverick | Winner |
|---|---|---|---|
| Overall Score | 80 | 80 | Llama 4 Maverick |
| Rank | #27 | #26 | Llama 4 Maverick |
| Quality Rank | #27 | #26 | Llama 4 Maverick |
| Adoption Rank | #27 | #26 | Llama 4 Maverick |
| Parameters | 27B | -- | -- |
| Context Window | 8K | 1049K | Llama 4 Maverick |
| Pricing | $0.65/$0.65/M | $0.15/$0.60/M | -- |
| Signal Scores | |||
| Capabilities | 33 | 67 | Llama 4 Maverick |
| Benchmarks | 83 | 80 | Gemma 2 27B |
| Pricing | 1 | 1 | Gemma 2 27B |
| Context window size | 62 | 96 | Llama 4 Maverick |
| Recency | 18 | 67 | Llama 4 Maverick |
| Output Capacity | 55 | 70 | Llama 4 Maverick |
Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Here's what the scores mean for these two models:
Scores 80/100 (rank #27), placing it in the top 91% of all 290 models tracked.
Scores 80/100 (rank #26), placing it in the top 91% of all 290 models tracked.
With only a 0-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.
Llama 4 Maverick offers 42% better value per quality point. At 1M tokens/day, you'd spend $11.25/month with Llama 4 Maverick vs $19.50/month with Gemma 2 27B - a $8.25 monthly difference.
Both models have comparable response speeds. For most applications, the latency difference is negligible.
When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.
Code generation & review
Higher benchmark score (0/100) indicates stronger performance on coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Faster response time (speed score 0/100) is critical for user-facing chat. Llama 4 Maverick also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (1049K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.60/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (80/100) correlates with better nuance, coherence, and style in long-form content
Image understanding & OCR
Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly
Gemma 2 27B and Llama 4 Maverick are extremely close in overall performance (only 0.20000000000000284 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Gemma 2 27B
Marginally better benchmark scores; both are excellent
Best for Cost
Llama 4 Maverick
42% lower pricing; better value at scale
Best for Reliability
Gemma 2 27B
Higher uptime and faster response speeds
Best for Prototyping
Gemma 2 27B
Stronger community support and better developer experience
Best for Production
Gemma 2 27B
Wider enterprise adoption and proven at scale
by Google
| Capability | Gemma 2 27B | Llama 4 Maverick |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Meta
Llama 4 Maverick saves you $0.9600/month
That's 49% cheaper than Gemma 2 27B at 1,000 tokens/request and 100 requests/day.
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | Gemma 2 27B | Llama 4 Maverick |
|---|---|---|
| Context Window | 8K | 1.0M |
| Max Output Tokens | 2,048 | 16,384 |
| Open Source | Yes | Yes |
| Created | Jul 13, 2024 | Apr 5, 2025 |
Llama 4 Maverick scores 80/100 (rank #26) compared to Gemma 2 27B's 80/100 (rank #27), giving it a 0-point advantage. Llama 4 Maverick is the stronger overall choice, though Gemma 2 27B may excel in specific areas like certain benchmarks.
Gemma 2 27B is ranked #27 and Llama 4 Maverick is ranked #26 out of 290+ AI models. Rankings use a composite score combining benchmark performance (90%) from MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations, with capabilities and context window as tiebreakers (10%). Scores update hourly.
Llama 4 Maverick is cheaper at $0.60/M output tokens vs Gemma 2 27B's $0.65/M output tokens - 1.1x more expensive. Input token pricing: Gemma 2 27B at $0.65/M vs Llama 4 Maverick at $0.15/M.
Llama 4 Maverick has a larger context window of 1,048,576 tokens compared to Gemma 2 27B's 8,192 tokens. A larger context window means the model can process longer documents and conversations.