| Signal | Gemma 4 31B | Delta | Llama 3.1 8B Instruct |
|---|---|---|---|
Capabilities | 67 | +17 | |
Pricing | 0 | +0 | |
Context window size | 86 | +19 | |
Recency | 100 | +80 | |
Output Capacity | 85 | +15 | |
Benchmarks | 0 | -40 | |
| Overall Result | 5 wins | of 6 | 1 wins |
3
days higher
1
days
26
days higher
Meta
Llama 3.1 8B Instruct saves you $29.50/month
That's $354.00/year compared to Gemma 4 31B at your current usage level of 100K calls/month.
| Metric | Gemma 4 31B | Llama 3.1 8B Instruct | Winner |
|---|---|---|---|
| Overall Score | 40 | 42 | Llama 3.1 8B Instruct |
| Rank | #118 | #116 | Llama 3.1 8B Instruct |
| Quality Rank | #118 | #116 | Llama 3.1 8B Instruct |
| Adoption Rank | #118 | #116 | Llama 3.1 8B Instruct |
| Parameters | 31B | 8B | -- |
| Context Window | 262K | 16K | Gemma 4 31B |
| Pricing | $0.14/$0.40/M | $0.02/$0.05/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 50 | Gemma 4 31B |
| Pricing | 0 | 0 | Gemma 4 31B |
| Context window size | 86 | 67 | Gemma 4 31B |
| Recency | 100 | 20 | Gemma 4 31B |
| Output Capacity | 85 | 70 | Gemma 4 31B |
| Benchmarks | -- | 40 | Llama 3.1 8B Instruct |
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 40/100 (rank #118), placing it in the top 60% of all 290 models tracked.
Scores 42/100 (rank #116), placing it in the top 60% of all 290 models tracked.
With only a 2-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 3.1 8B Instruct offers 87% better value per quality point. At 1M tokens/day, you'd spend $1.05/month with Llama 3.1 8B Instruct vs $8.10/month with Gemma 4 31B - a $7.05 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 3.1 8B Instruct also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (262K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.05/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (42/100) 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 4 31B and Llama 3.1 8B Instruct are extremely close in overall performance (only 2.200000000000003 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Gemma 4 31B
Marginally better benchmark scores; both are excellent
Best for Cost
Llama 3.1 8B Instruct
87% lower pricing; better value at scale
Best for Reliability
Gemma 4 31B
Higher uptime and faster response speeds
Best for Prototyping
Gemma 4 31B
Stronger community support and better developer experience
Best for Production
Gemma 4 31B
Wider enterprise adoption and proven at scale
by Google
| Capability | Gemma 4 31B | Llama 3.1 8B Instruct |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
Meta
Llama 3.1 8B Instruct saves you $0.6360/month
That's 87% cheaper than Gemma 4 31B 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 4 31B | Llama 3.1 8B Instruct |
|---|---|---|
| Context Window | 262K | 16K |
| Max Output Tokens | 131,072 | 16,384 |
| Open Source | Yes | Yes |
| Created | Apr 2, 2026 | Jul 23, 2024 |
Llama 3.1 8B Instruct scores 42/100 (rank #116) compared to Gemma 4 31B's 40/100 (rank #118), giving it a 2-point advantage. Llama 3.1 8B Instruct is the stronger overall choice, though Gemma 4 31B may excel in specific areas like certain benchmarks.
Gemma 4 31B is ranked #118 and Llama 3.1 8B Instruct is ranked #116 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 3.1 8B Instruct is cheaper at $0.05/M output tokens vs Gemma 4 31B's $0.40/M output tokens - 8.0x more expensive. Input token pricing: Gemma 4 31B at $0.14/M vs Llama 3.1 8B Instruct at $0.02/M.
Gemma 4 31B has a larger context window of 262,144 tokens compared to Llama 3.1 8B Instruct's 16,384 tokens. A larger context window means the model can process longer documents and conversations.