Gemma 4 26B A4B (free) is free for input tokens while Qwen3.5-Flash costs $0.07 per 1M tokens.
API cost decision in 10 seconds
Qwen3.5-Flash vs Gemma 4 26B A4B (free)
Pick Gemma 4 26B A4B (free) for lower cost; pick Qwen3.5-Flash 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 Gemma 4 26B A4B (free) for lower cost; pick Qwen3.5-Flash only if the larger context window matters more.
On the standard 1M input plus 500K output workload, Gemma 4 26B A4B (free) is estimated at $0 vs $0.2 for Qwen3.5-Flash, saving $0.2 (100% lower).
Cost-first pickGemma 4 26B A4B (free)
Context-first pickQwen3.5-Flash
Sample savings$0.2100%
10x traffic gap$1.95
Qwen3.5-Flash has more context, but Gemma 4 26B A4B (free) saves $0.2 on the standard workload. At 10x that traffic, the same price gap is about $1.95. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
Gemma 4 26B A4B (free) stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | Qwen3.5-Flash | Gemma 4 26B A4B (free) |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | Gemma 4 26B A4B (free) | $0.46 | $0 |
| Balanced workload | 1M input + 1M output | Gemma 4 26B A4B (free) | $0.33 | $0 |
| Output-heavy chatbot | 1M input + 5M output | Gemma 4 26B A4B (free) | $1.36 | $0 |
Gemma 4 26B A4B (free) is free for output tokens while Qwen3.5-Flash costs $0.26 per 1M tokens.
Qwen3.5-Flash has 737.86K more context (3.81x larger).
Gemma 4 26B A4B (free) is free for the standard workload while the other model is estimated at $0.2.
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 26B A4B (free) has the lower input price; Gemma 4 26B A4B (free) has the lower output price; Qwen3.5-Flash offers the larger context window. For the 1M input plus 500K output sample, Gemma 4 26B A4B (free) is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $0.2 for Qwen3.5-Flash and $0 for Gemma 4 26B A4B (free).
Choose Qwen3.5-Flash when you care most about larger context window.
Choose Gemma 4 26B A4B (free) when you care most about lower input-token price, and lower output-token price.
- On the standard 1M input plus 500K output workload, Gemma 4 26B A4B (free) is estimated at $0 vs $0.2 for Qwen3.5-Flash, saving $0.2 (100% lower).
- Gemma 4 26B A4B (free) is free for the standard workload while the other model is estimated at $0.2.
- Gemma 4 26B A4B (free) is free for input tokens while Qwen3.5-Flash costs $0.07 per 1M tokens.
- Gemma 4 26B A4B (free) is free for output tokens while Qwen3.5-Flash costs $0.26 per 1M tokens.
- Qwen3.5-Flash has 737.86K more context (3.81x larger).
| Feature | Qwen3.5-Flash (Qwen) | Gemma 4 26B A4B (free) (Google) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.065 | $0 |
| Completion Price per 1M tokens | $0.26 | $0 |
| Sample Workload Cost 1M input + 500K output | $0.2 | $0 |
| Context Window | 1M | 262.14K |
| Release Date | ||
| Popularity | #25 | #148 |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | Gemma 4 26B A4B (free) | On the standard 1M input plus 500K output workload, Gemma 4 26B A4B (free) is estimated at $0 vs $0.2 for Qwen3.5-Flash, saving $0.2 (100% lower). |
| High-volume input processing | Gemma 4 26B A4B (free) | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | Gemma 4 26B A4B (free) | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | Qwen3.5-Flash | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
- Qwen3 Next 80B A3B Instruct (free) can replace Qwen3.5-Flash when lower sample workload cost matters most: $0.
- Qwen3 Coder 480B A35B (free) can replace Qwen3.5-Flash when lower sample workload cost matters most: $0.
- Qwen2.5 7B Instruct can replace Qwen3.5-Flash when lower sample workload cost matters most: $0.09.
- Qwen3.5-9B can replace Qwen3.5-Flash when lower sample workload cost matters most: $0.11.
- 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.
- DeepSeek V4 Flash (free) 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 hubsQwen catalog
Review all tracked Qwen models before deciding whether this matchup is the right shortlist.
Open Qwen modelsGoogle catalog
Check other Google models with comparable pricing, context, or release timing.
Open Google modelsThe Qwen3.5 native vision-language Flash models are built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. Compared to the...
Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind. Despite 25.2B total parameters, only 3.8B activate per token during inference — delivering near-31B quality at...