Gemma 4 31B (free) is free for input tokens while Llama 3.1 8B Instruct costs $0.02 per 1M tokens.
API cost decision in 10 seconds
Llama 3.1 8B Instruct vs Gemma 4 31B (free)
Pick Gemma 4 31B (free) when budget and context both matter.
Page updated:
Data confirmed:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick Gemma 4 31B (free) when budget and context both matter.
On the standard 1M input plus 500K output workload, Gemma 4 31B (free) is estimated at $0 vs $0.04 for Llama 3.1 8B Instruct, saving $0.04 (100% lower).
Cost-first pickGemma 4 31B (free)
Context-first pickGemma 4 31B (free)
Sample savings$0.04100%
10x traffic gap$0.45
Gemma 4 31B (free) is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $0.45. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
Gemma 4 31B (free) stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | Llama 3.1 8B Instruct | Gemma 4 31B (free) |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | Gemma 4 31B (free) | $0.12 | $0 |
| Balanced workload | 1M input + 1M output | Gemma 4 31B (free) | $0.07 | $0 |
| Output-heavy chatbot | 1M input + 5M output | Gemma 4 31B (free) | $0.27 | $0 |
Gemma 4 31B (free) is free for output tokens while Llama 3.1 8B Instruct costs $0.05 per 1M tokens.
Gemma 4 31B (free) has 131.07K more context (2x larger).
Gemma 4 31B (free) is free for the standard workload while the other model is estimated at $0.04.
Estimate your workload cost
Your Workload Cost
This estimate uses normalized public API pricing per 1M tokens. It is a planning aid, not a billing quote. Verify provider pricing, limits, and terms before production use.
Quick Decision
Gemma 4 31B (free) has the lower input price; Gemma 4 31B (free) has the lower output price; Gemma 4 31B (free) offers the larger context window. For the 1M input plus 500K output sample, Gemma 4 31B (free) is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $0.04 for Llama 3.1 8B Instruct and $0 for Gemma 4 31B (free).
Choose Llama 3.1 8B Instruct when its provider, model quality, latency, or availability is more important than the numeric price/context winner.
Choose Gemma 4 31B (free) when you care most about lower input-token price, lower output-token price, and larger context window.
- On the standard 1M input plus 500K output workload, Gemma 4 31B (free) is estimated at $0 vs $0.04 for Llama 3.1 8B Instruct, saving $0.04 (100% lower).
- Gemma 4 31B (free) is free for the standard workload while the other model is estimated at $0.04.
- Gemma 4 31B (free) is free for input tokens while Llama 3.1 8B Instruct costs $0.02 per 1M tokens.
- Gemma 4 31B (free) is free for output tokens while Llama 3.1 8B Instruct costs $0.05 per 1M tokens.
- Gemma 4 31B (free) has 131.07K more context (2x larger).
| Feature | Llama 3.1 8B Instruct (Meta) | Gemma 4 31B (free) (Google) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.02 | $0 |
| Completion Price per 1M tokens | $0.05 | $0 |
| Sample Workload Cost 1M input + 500K output | $0.04 | $0 |
| Context Window | 131.07K | 262.14K |
| Release Date | ||
| Popularity | #40 | #105 |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | Gemma 4 31B (free) | On the standard 1M input plus 500K output workload, Gemma 4 31B (free) is estimated at $0 vs $0.04 for Llama 3.1 8B Instruct, saving $0.04 (100% lower). |
| High-volume input processing | Gemma 4 31B (free) | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | Gemma 4 31B (free) | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | Gemma 4 31B (free) | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
- Llama 3.3 70B Instruct (free) can replace Llama 3.1 8B Instruct when lower sample workload cost matters most: $0.
- Llama 3.2 3B Instruct (free) can replace Llama 3.1 8B Instruct when lower sample workload cost matters most: $0.
- Owl Alpha offers 1.05M context with $0 sample workload cost.
- DeepSeek V4 Flash (free) offers 1.05M context with $0 sample workload cost.
- Lyria 3 Clip Preview offers 1.05M context with $0 sample workload cost.
- Lyria 3 Pro Preview offers 1.05M context with $0 sample workload cost.
- DeepSeek V4 Flash · DeepSeek · #1
- Hy3 preview · Tencent · #2
- Claude Opus 4.7 · Anthropic · #3
- Claude Sonnet 4.6 · Anthropic · #4
Cheaper alternatives
Review low-cost models sorted by a standard 1M input plus 500K output workload.
Open cheapest modelsLarger context alternatives
Find models with larger context windows for RAG, long documents, and codebase review.
Open largest context modelsProvider catalogs
Compare models within provider hubs before choosing a final API vendor.
Open provider hubsMeta catalog
Review all tracked Meta models before deciding whether this matchup is the right shortlist.
Open Meta modelsGoogle catalog
Check other Google models with comparable pricing, context, or release timing.
Open Google modelsMeta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 8B instruct-tuned version is fast and efficient. It has demonstrated strong performance compared to...
Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking/reasoning mode, native function...