API cost decision in 10 seconds

Gemma 4 31B vs MiniMax M2-her

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

Pricing data updated: 2026-05-26T11:08:00Z Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

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

On the standard 1M input plus 500K output workload, Gemma 4 31B is estimated at $0.3 vs $0.9 for MiniMax M2-her, saving $0.59 (66.1% lower).

Cost-first pickGemma 4 31B

Context-first pickGemma 4 31B

Sample savings$0.5966.1%

10x traffic gap$5.95

Gemma 4 31B is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $5.95. 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 stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shape	Token mix	Better pick	Gemma 4 31B	MiniMax M2-her
Input-heavy / RAG	5M input + 500K output	Gemma 4 31B	$0.78	$2.1
Balanced workload	1M input + 1M output	Gemma 4 31B	$0.49	$1.5
Output-heavy chatbot	1M input + 5M output	Gemma 4 31B	$1.97	$6.3

Cheaper input Gemma 4 31B $0.12 vs $0.3 / 1M

Gemma 4 31B is $0.18 cheaper per 1M input tokens (60% lower; 2.5x difference).

Cheaper output Gemma 4 31B $0.37 vs $1.2 / 1M

Gemma 4 31B is $0.83 cheaper per 1M output tokens (69.2% lower; 3.24x difference).

Larger context Gemma 4 31B 262.14K vs 65.54K

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

Sample workload Gemma 4 31B $0.3 vs $0.9

Gemma 4 31B is $0.59 cheaper on the standard workload (66.1% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.

Monthly input tokens Monthly output tokens

Gemma 4 31B 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 has the lower input price; Gemma 4 31B has the lower output price; Gemma 4 31B offers the larger context window. For the 1M input plus 500K output sample, Gemma 4 31B 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 $0.9 for MiniMax M2-her.

Best Fit

Choose Gemma 4 31B 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 is estimated at $0.3 vs $0.9 for MiniMax M2-her, saving $0.59 (66.1% lower).
Gemma 4 31B is $0.59 cheaper on the standard workload (66.1% lower).
Gemma 4 31B is $0.18 cheaper per 1M input tokens (60% lower; 2.5x difference).
Gemma 4 31B is $0.83 cheaper per 1M output tokens (69.2% lower; 3.24x difference).
Gemma 4 31B has 196.61K more context (4x larger).

Head-to-Head Specs

Feature	Gemma 4 31B (Google)	MiniMax M2-her (MiniMax)
Input Price prompt tokens per 1M	$0.12	$0.3
Completion Price per 1M tokens	$0.37	$1.2
Sample Workload Cost 1M input + 500K output	$0.3	$0.9
Context Window	262.14K	65.54K
Release Date	2026-04-02	2026-01-23

Use-Case Decision Matrix

Use case	Better pick	Why
Budget-constrained production	Gemma 4 31B	On the standard 1M input plus 500K output workload, Gemma 4 31B is estimated at $0.3 vs $0.9 for MiniMax M2-her, saving $0.59 (66.1% lower).
High-volume input processing	Gemma 4 31B	Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbots	Gemma 4 31B	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

Same-provider lower-cost swaps

Gemma 4 26B A4B (free) can replace Gemma 4 31B when lower sample workload cost matters most: $0.
Gemma 4 31B (free) 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.
Lyria 3 Clip Preview can replace Gemma 4 31B when lower sample workload cost matters most: $0.

Larger context near this budget

Llama 4 Scout offers 10M context with $0.23 sample workload cost.
Owl Alpha offers 1.05M context with $0 sample workload cost.
Gemini 3.1 Flash Lite offers 1.05M context with $1 sample workload cost.
DeepSeek V4 Pro offers 1.05M context with $0.87 sample workload cost.

Popular competitors

No popular competitor is currently available.

Cheaper alternatives

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

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Larger context alternatives

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

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Provider catalogs

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Google catalog

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

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MiniMax catalog

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

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Gemma 4 31B

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...