Qwen2.5 7B Instruct is $0.08 cheaper per 1M input tokens (66.7% lower; 3x difference).
API cost decision in 10 seconds
Gemma 4 31B vs Qwen2.5 7B Instruct
Pick Qwen2.5 7B Instruct for lower cost; pick Gemma 4 31B only if the larger context window matters more.
Page updated:
Data confirmed:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick Qwen2.5 7B Instruct for lower cost; pick Gemma 4 31B only if the larger context window matters more.
On the standard 1M input plus 500K output workload, Qwen2.5 7B Instruct is estimated at $0.09 vs $0.3 for Gemma 4 31B, saving $0.21 (70.5% lower).
Cost-first pickQwen2.5 7B Instruct
Context-first pickGemma 4 31B
Sample savings$0.2170.5%
10x traffic gap$2.15
Gemma 4 31B has more context, but Qwen2.5 7B Instruct saves $0.21 on the standard workload. At 10x that traffic, the same price gap is about $2.15. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
Qwen2.5 7B Instruct stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | Gemma 4 31B | Qwen2.5 7B Instruct |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | Qwen2.5 7B Instruct | $0.78 | $0.25 |
| Balanced workload | 1M input + 1M output | Qwen2.5 7B Instruct | $0.49 | $0.14 |
| Output-heavy chatbot | 1M input + 5M output | Qwen2.5 7B Instruct | $1.97 | $0.54 |
Qwen2.5 7B Instruct is $0.27 cheaper per 1M output tokens (73% lower; 3.7x difference).
Gemma 4 31B has 131.07K more context (2x larger).
Qwen2.5 7B Instruct is $0.21 cheaper on the standard workload (70.5% lower).
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
Qwen2.5 7B Instruct has the lower input price; Qwen2.5 7B Instruct has the lower output price; Gemma 4 31B offers the larger context window. For the 1M input plus 500K output sample, Qwen2.5 7B Instruct is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $0.3 for Gemma 4 31B and $0.09 for Qwen2.5 7B Instruct.
Choose Gemma 4 31B when you care most about larger context window.
Choose Qwen2.5 7B Instruct when you care most about lower input-token price, and lower output-token price.
- On the standard 1M input plus 500K output workload, Qwen2.5 7B Instruct is estimated at $0.09 vs $0.3 for Gemma 4 31B, saving $0.21 (70.5% lower).
- Qwen2.5 7B Instruct is $0.21 cheaper on the standard workload (70.5% lower).
- Qwen2.5 7B Instruct is $0.08 cheaper per 1M input tokens (66.7% lower; 3x difference).
- Qwen2.5 7B Instruct is $0.27 cheaper per 1M output tokens (73% lower; 3.7x difference).
- Gemma 4 31B has 131.07K more context (2x larger).
| Feature | Gemma 4 31B (Google) | Qwen2.5 7B Instruct (Qwen) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.12 | $0.04 |
| Completion Price per 1M tokens | $0.37 | $0.1 |
| Sample Workload Cost 1M input + 500K output | $0.3 | $0.09 |
| Context Window | 262.14K | 131.07K |
| Release Date | ||
| Popularity | #27 | #134 |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | Qwen2.5 7B Instruct | On the standard 1M input plus 500K output workload, Qwen2.5 7B Instruct is estimated at $0.09 vs $0.3 for Gemma 4 31B, saving $0.21 (70.5% lower). |
| High-volume input processing | Qwen2.5 7B Instruct | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | Qwen2.5 7B Instruct | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | Gemma 4 31B | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
- Gemma 4 31B (free) can replace Gemma 4 31B when lower sample workload cost matters most: $0.
- Gemma 4 26B A4B (free) can replace Gemma 4 31B when lower sample workload cost matters most: $0.
- Lyria 3 Clip Preview can replace Gemma 4 31B when lower sample workload cost matters most: $0.
- Lyria 3 Pro Preview can replace Gemma 4 31B when lower sample workload cost matters most: $0.
- Llama 4 Scout offers 10M context with $0.23 sample workload cost.
- Owl Alpha offers 1.05M context with $0 sample workload cost.
- DeepSeek V4 Flash offers 1.05M context with $0.2 sample workload cost.
- Gemini 2.5 Flash Lite offers 1.05M context with $0.3 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 hubsGoogle catalog
Review all tracked Google models before deciding whether this matchup is the right shortlist.
Open Google modelsQwen catalog
Check other Qwen models with comparable pricing, context, or release timing.
Open Qwen modelsGemma 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...
Qwen2.5 7B is the latest series of Qwen large language models. Qwen2.5 brings the following improvements upon Qwen2: - Significantly more knowledge and has greatly improved capabilities in coding and...