API cost decision in 10 seconds

Gemma 4 31B (free) vs MiniMax M2-her

Pick Gemma 4 31B (free) when budget and context both matter.

Pricing data updated:  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 $0.9 for MiniMax M2-her, saving $0.9 (100% lower).

Cost-first pickGemma 4 31B (free)
Context-first pickGemma 4 31B (free)
Sample savings$0.9100%
10x traffic gap$9

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 $9. 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 pickGemma 4 31B (free)MiniMax M2-her
Input-heavy / RAG5M input + 500K outputGemma 4 31B (free)$0$2.1
Balanced workload1M input + 1M outputGemma 4 31B (free)$0$1.5
Output-heavy chatbot1M input + 5M outputGemma 4 31B (free)$0$6.3
Cheaper input Gemma 4 31B (free) $0 vs $0.3 / 1M

Gemma 4 31B (free) is free for input tokens while MiniMax M2-her costs $0.3 per 1M tokens.

Cheaper output Gemma 4 31B (free) $0 vs $1.2 / 1M

Gemma 4 31B (free) is free for output tokens while MiniMax M2-her costs $1.2 per 1M tokens.

Larger context Gemma 4 31B (free) 262.14K vs 65.54K

Gemma 4 31B (free) has 196.61K more context (4x larger).

Sample workload Gemma 4 31B (free) $0 vs $0.9

Gemma 4 31B (free) is free for the standard workload while the other model is estimated at $0.9.

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
Gemma 4 31B (free) Calculating… Estimated API cost
MiniMax M2-her 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; 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 for Gemma 4 31B (free) and $0.9 for MiniMax M2-her.

Best Fit

Choose Gemma 4 31B (free) when you care most about lower input-token price, lower output-token price, and larger context window.

Choose MiniMax M2-her when its provider, model quality, latency, or availability is more important than the numeric price/context winner.

Decision Notes
  • On the standard 1M input plus 500K output workload, Gemma 4 31B (free) is estimated at $0 vs $0.9 for MiniMax M2-her, saving $0.9 (100% lower).
  • Gemma 4 31B (free) is free for the standard workload while the other model is estimated at $0.9.
  • Gemma 4 31B (free) is free for input tokens while MiniMax M2-her costs $0.3 per 1M tokens.
  • Gemma 4 31B (free) is free for output tokens while MiniMax M2-her costs $1.2 per 1M tokens.
  • Gemma 4 31B (free) has 196.61K more context (4x larger).
Head-to-Head Specs
FeatureGemma 4 31B (free)
(Google)
MiniMax M2-her
(MiniMax)
Input Price
prompt tokens per 1M
$0$0.3
Completion Price
per 1M tokens
$0$1.2
Sample Workload Cost
1M input + 500K output
$0$0.9
Context Window262.14K65.54K
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 $0.9 for MiniMax M2-her, saving $0.9 (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 workGemma 4 31B (free)A larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Same-provider lower-cost swaps
  • MiniMax M2.5 (free) can replace MiniMax M2-her when lower sample workload cost matters most: $0.
  • MiniMax M2.5 can replace MiniMax M2-her when lower sample workload cost matters most: $0.72.
  • MiniMax-01 can replace MiniMax M2-her when lower sample workload cost matters most: $0.75.
  • MiniMax M2 can replace MiniMax M2-her when lower sample workload cost matters most: $0.76.
Larger context near this budget
Popular competitors
  • No popular competitor is currently available.

Cheaper alternatives

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Larger context alternatives

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Provider catalogs

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Google catalog

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MiniMax catalog

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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...

MiniMax M2-her

MiniMax M2-her is a dialogue-first large language model built for immersive roleplay, character-driven chat, and expressive multi-turn conversations. Designed to stay consistent in tone and personality, it supports rich message...