A capable open-weight budget model hamstrung by a frustratingly small context window.
58
Coding
62
Writing
48
Research
0
Images
88
Value
18
Long Context
Use this when
Lightweight text tasks, classification, and summarization where cost matters more than frontier-level quality.
Skip this if
You need to process documents longer than a few pages, require strong reasoning, or need multimodal (image/audio) inputs.
Pricing
$0.03/1M in
$0.09/1M out
→0%since May 2026
Context
8k tokens
Speed
Very fast
Pricing reflects API access through third-party providers; Google also offers Gemma 2 9B weights for free download and self-hosting. The 8,192 token limit is a hard architectural constraint of this version.
Recommendations are made independently based on real-world use and public benchmarks. See our disclosures for details.
Compare alternatives
Similar models worth checking before you commit.
GoogleBudget
Gemma 4 26B A4B
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
Best for cost-sensitive applications needing long-context processing with reasonable quality, such as document summarization pipelines or lightweight coding assistants.
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.
Gemma 4 31B is Google's open-weight instruction-tuned model offering a strong balance of capability and cost efficiency at just $0.14/$0.40 per million tokens. It features a 262K context window and is designed for developers who need capable on-premise or API-hosted inference without flagship pricing.
Verdict
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.
Quality score
66%
Pricing
$0.14/1M in
$0.40/1M out
Speed
Fast
Best for cost-conscious developers needing a capable open-weight model for coding assistance, summarization, and document analysis at scale.
Context
262k tokens
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.
Open WeightBudgetLong ContextCodingSelf-Hostable
Best for
Cost-conscious developers needing a capable open-weight model for coding assistance, summarization, and document analysis at scale.
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
Best for high-volume, latency-sensitive applications like chatbots, classification, data extraction, and agentic tool use where speed and cost matter more than peak reasoning depth.
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.
Google: Gemma 2 9B is best for lightweight text tasks, classification, and summarization where cost matters more than frontier-level quality.. It is a strong fit when that workflow matters more than the tradeoffs around budget pricing and very fast speed.
When should I avoid Google: Gemma 2 9B?
You need to process documents longer than a few pages, require strong reasoning, or need multimodal (image/audio) inputs.
What is a cheaper alternative to Google: Gemma 2 9B?
Meta: Llama 3.1 8B Instruct is the lower-cost option to compare first when you want a similar workflow fit with less token spend.
What is a faster alternative to Google: Gemma 2 9B?
Gemma 4 26B A4B is the better pick when response time matters more than maximum depth or premium quality.
Newsletter
Get notified when Google: Gemma 2 9B pricing changes
We track pricing daily. When this model drops or spikes, you'll know first.
No spam. Useful updates only. Affiliate disclosures always clearly labeled.