API cost decision in 10 seconds

Qwen3.6 35B A3B vs Gemma 4 31B (free)

Pick Gemma 4 31B (free) when budget is the priority.

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 is the priority.

On the standard 1M input plus 500K output workload, Gemma 4 31B (free) is estimated at $0 vs $0.65 for Qwen3.6 35B A3B, saving $0.65 (100% lower).

Cost-first pickGemma 4 31B (free)
Context-first pickBoth models
Sample savings$0.65100%
10x traffic gap$6.5

The reported context window is tied, so cost and provider fit carry more weight. At 10x that traffic, the same price gap is about $6.5. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Gemma 4 31B (free) stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shapeToken mixBetter pickQwen3.6 35B A3BGemma 4 31B (free)
Input-heavy / RAG5M input + 500K outputGemma 4 31B (free)$1.25$0
Balanced workload1M input + 1M outputGemma 4 31B (free)$1.15$0
Output-heavy chatbot1M input + 5M outputGemma 4 31B (free)$5.15$0
Cheaper input Gemma 4 31B (free) $0.15 vs $0 / 1M

Gemma 4 31B (free) is free for input tokens while Qwen3.6 35B A3B costs $0.15 per 1M tokens.

Cheaper output Gemma 4 31B (free) $1 vs $0 / 1M

Gemma 4 31B (free) is free for output tokens while Qwen3.6 35B A3B costs $1 per 1M tokens.

Larger context Tie 262.14K vs 262.14K

Both models report the same context window at 262.14K tokens.

Sample workload Gemma 4 31B (free) $0.65 vs $0

Gemma 4 31B (free) is free for the standard workload while the other model is estimated at $0.65.

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
Qwen3.6 35B A3B Calculating… Estimated API cost
Gemma 4 31B (free) Calculating… Estimated API cost
Cheaper for this workload Calculating… Difference: calculating…

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

Verdict

Gemma 4 31B (free) has the lower input price; Gemma 4 31B (free) has the lower output price; both models report the same 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 $0.65 for Qwen3.6 35B A3B and $0 for Gemma 4 31B (free).

Best Fit

Choose Qwen3.6 35B A3B 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, and lower output-token price.

Decision Notes
  • On the standard 1M input plus 500K output workload, Gemma 4 31B (free) is estimated at $0 vs $0.65 for Qwen3.6 35B A3B, saving $0.65 (100% lower).
  • Gemma 4 31B (free) is free for the standard workload while the other model is estimated at $0.65.
  • Gemma 4 31B (free) is free for input tokens while Qwen3.6 35B A3B costs $0.15 per 1M tokens.
  • Gemma 4 31B (free) is free for output tokens while Qwen3.6 35B A3B costs $1 per 1M tokens.
  • Both models report the same context window at 262.14K tokens.
Head-to-Head Specs
FeatureQwen3.6 35B A3B
(Qwen)
Gemma 4 31B (free)
(Google)
Input Price
prompt tokens per 1M
$0.15$0
Completion Price
per 1M tokens
$1$0
Sample Workload Cost
1M input + 500K output
$0.65$0
Context Window262.14K262.14K
Release Date

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionGemma 4 31B (free)On the standard 1M input plus 500K output workload, Gemma 4 31B (free) is estimated at $0 vs $0.65 for Qwen3.6 35B A3B, saving $0.65 (100% lower).
High-volume input processingGemma 4 31B (free)Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsGemma 4 31B (free)Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workTieA larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Larger context near this budget

Cheaper alternatives

Review low-cost models sorted by a standard 1M input plus 500K output workload.

Open cheapest models

Larger context alternatives

Find models with larger context windows for RAG, long documents, and codebase review.

Open largest context models

Provider catalogs

Compare models within provider hubs before choosing a final API vendor.

Open provider hubs

Qwen catalog

Review all tracked Qwen models before deciding whether this matchup is the right shortlist.

Open Qwen models

Google catalog

Check other Google models with comparable pricing, context, or release timing.

Open Google models
Qwen3.6 35B A3B

Qwen3.6-35B-A3B is an open-weight multimodal model from Alibaba Cloud with 35 billion total parameters and 3 billion active parameters per token. It uses a hybrid sparse mixture-of-experts architecture combining Gated...

Gemma 4 31B (free)

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...