A well-priced, long-context open-weight model that's ideal for high-volume developer workloads but won't match frontier models on complex reasoning.
74
Coding
68
Writing
72
Research
0
Images
88
Value
82
Long Context
Use this when
Cost-conscious developers needing a capable open-weight model for coding assistance, summarization, and document analysis at scale.
Skip this if
You need advanced multimodal input processing, cutting-edge reasoning chains, or the highest-quality creative writing outputs — spend up for Gemini 2.5 Pro or Claude Sonnet 4.6 instead.
Pricing
$0.39/1M in
$0.97/1M out
↑179%since Jun 2026
Context
262k tokens
Speed
Fast
As an open-weight model, Gemma 4 31B can be self-hosted via Ollama or Hugging Face in addition to Google's API. Pricing shown is for hosted inference. No image input capability confirmed at launch.
Extremely competitive pricing — $0.14 input makes it cheaper than Claude Haiku and Gemini Flash for most workloads
262K context window rivals much more expensive models like GPT-4o and Claude Sonnet 4.6
Open-weight architecture allows self-hosting for privacy-sensitive or latency-critical deployments
Solid instruction-following and code generation for its size class
Weaknesses
At 31B parameters, complex multi-step reasoning lags behind frontier models like Gemini 2.5 Pro or GPT-5.4
No native multimodal (image/audio) input support limits use cases compared to Gemini Flash
Occasional factual hallucinations on niche knowledge domains typical of sub-70B models
Real-world use cases
What people actually use Gemma 4 31B for.
Ingesting and summarizing 200-page legal or technical documents within a single 262K context pass
Generating boilerplate code, unit tests, and API integrations for web applications at low per-request cost
Running high-volume content moderation or text classification pipelines where budget is a primary constraint
How Gemma 4 31B compares
The nearest models people weigh against it, and what actually separates them.
vs Gemma 4 26B A4B — Against Gemma 4 26B A4B (Google), Gemma 4 31B costs about 61% more per token. Gemma 4 26B A4B is the one to check first if the price difference matters more than the ceiling.
vs Claude 3.5 Haiku — Against Claude 3.5 Haiku (Anthropic), Gemma 4 31B runs about 72% cheaper per token, takes 1.3x the context and answers slower. Which one wins depends on whether context depth or latency is your constraint.
vs GPT-5 Mini — Against GPT-5 Mini (OpenAI), Gemma 4 31B runs about 40% cheaper per token, gives up 1.5x on context and answers slower. Which one wins depends on whether context depth or latency is your constraint.
Price History
Gemma 4 31B pricing over time
↑179% since Jun 3
90 data points · tracked daily since Jun 3, 2026
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Start using Gemma 4 31B
Cost-conscious developers needing a capable open-weight model for coding assistance, summarization, and document analysis at scale.. Start free — no card required.
Gemma 4 26B A4B is a sparse mixture-of-experts open model from Google, activating only ~4B parameters per forward pass despite having 26B total parameters. It offers a 262K context window at budget pricing, making it one of the more capable open-weight models for its cost tier.
Verdict
A lean, fast, and surprisingly capable budget model best suited for high-volume text tasks where cost efficiency trumps peak quality.
Quality score
59%
Pricing
$0.13/1M in
$0.40/1M out
Speed
Fast
4/5 speed
Context
262k tokens
As an open-weight model, Gemma 4 26B can also be self-hosted, making API pricing largely irrelevant at scale. The 'A4B' suffix denotes the active parameter count in its MoE configuration. Listed as superseding Gemini 3 Flash Preview, though Gemini 2.0 Flash remains a stronger hosted alternative.
Open-weightBudgetMoELong ContextGoogle
Best for
Cost-sensitive applications needing long-context processing with reasonable quality, such as document summarization pipelines or lightweight coding assistants.
Claude 3.5 Haiku is Anthropic's fastest and most affordable model in the Claude 3.5 family, designed for high-throughput tasks requiring quick responses without sacrificing Claude's core instruction-following quality. It handles a massive 200K context window while maintaining speed suitable for production pipelines.
Verdict
The fastest way to get Claude's quality in production — just don't confuse 'fast' with 'cheap'.
Quality score
64%
Pricing
$0.80/1M in
$4.00/1M out
Speed
Very fast
5/5 speed
Context
200k tokens
Output cost of $4/1M is notably higher than competing fast/mini models. Input cost at ~$0.80/1M is competitive. Best value emerges in input-heavy pipelines like document classification or RAG retrieval where output tokens are minimal.
High-volume, latency-sensitive applications like chatbots, classification, data extraction, and agentic tool use where speed and cost matter more than peak reasoning depth.
GPT-5 Mini is OpenAI's budget-tier distillation of GPT-5, designed for high-volume, cost-sensitive tasks that don't require full flagship reasoning depth. It supersedes GPT-4o with improved instruction following and a massively expanded 400K context window at a fraction of the cost.
Verdict
The new budget default for OpenAI API users: faster, cheaper, and smarter than GPT-4o with a context window that punches well above its price tier.
Quality score
66%
Pricing
$0.25/1M in
$2.00/1M out
Speed
Very fast
5/5 speed
Context
400k tokens
Output cost of $2/1M tokens is higher than some competing budget models (Gemini Flash at ~$0.60/1M output). At scale, output-heavy tasks may erode cost advantages — monitor token ratios carefully. Supersedes GPT-4o, which may be deprecated on a rolling basis.
BudgetFastLong ContextHigh VolumeOpenAI
Best for
High-volume production workloads — chatbots, summarization pipelines, and document Q&A — where cost efficiency matters more than peak reasoning.
Gemma 4 31B (Google) is now indexed. It supersedes Google: Gemini 3 Flash Preview. A well-priced, long-context open-weight model that's ideal for high-volume developer workloads but won't match frontier models on complex reasoning.
Gemma 4 31B costs $0.39 per million input tokens and $0.9700000000000001 per million output tokens on the API. A month of 10M input and 2M output tokens runs about $5.84 at list price, before any batch or caching discounts.
What is Gemma 4 31B best for?
Gemma 4 31B is best for cost-conscious developers needing a capable open-weight model for coding assistance, summarization, and document analysis at scale.. It is a strong fit when that workflow matters more than the tradeoffs around budget pricing and fast speed.
When should I avoid Gemma 4 31B?
You need advanced multimodal input processing, cutting-edge reasoning chains, or the highest-quality creative writing outputs — spend up for Gemini 2.5 Pro or Claude Sonnet 4.6 instead.
What is a cheaper alternative to Gemma 4 31B?
Gemma 4 26B A4B (Google) at $0.13/1M/1M input against Gemma 4 31B's $0.39/1M/1M — roughly 61% less per token all in. A lean, fast, and surprisingly capable budget model best suited for high-volume text tasks where cost efficiency trumps peak quality. Compare it first if Gemma 4 31B's pricing is the thing stopping you.
What is a faster alternative to Gemma 4 31B?
Claude 3.5 Haiku — very fast against Gemma 4 31B's fast, with 200k tokens of context. Worth the swap when response time is what your users notice rather than the last few points of reasoning depth.
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