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.
Extremely low cost at $0.03/$0.09 per 1M tokens — cheaper than most comparable small models
Strong instruction-following for its parameter count, competitive with Llama 3 8B and Mistral 7B
Open weights allow self-hosting and fine-tuning for specialized use cases
Reliable for structured output tasks like classification, extraction, and summarization
Weaknesses
8,192 token context window is restrictive — cannot handle long documents or extended conversations
Noticeably behind GPT-4o mini and Claude Haiku 3.5 on complex reasoning and multi-step coding tasks
No multimodal capabilities — text-only input and output
Real-world use cases
What people actually use Gemma 2 9B for.
Classifying customer support tickets into predefined categories at scale
Generating short product descriptions from structured data inputs
Fine-tuning on domain-specific data for a specialized text extraction pipeline
How Gemma 2 9B 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 2 9B runs about 77% cheaper per token, gives up 32x on context and answers faster. Take Gemma 2 9B unless you specifically need what Gemma 4 26B A4B does better.
vs Gemma 4 31B — Against Gemma 4 31B (Google), Gemma 2 9B runs about 91% cheaper per token, gives up 32x on context and answers faster. Take Gemma 2 9B unless you specifically need what Gemma 4 31B does better.
vs Claude 3.5 Haiku — Against Claude 3.5 Haiku (Anthropic), Gemma 2 9B runs about 98% cheaper per token and gives up 24.4x on context. Take Gemma 2 9B unless you specifically need what Claude 3.5 Haiku does better.
Price History
Gemma 2 9B pricing over time
→0% since May 31
90 data points · tracked daily since May 31, 2026
Ready to try it?
Start using Gemma 2 9B
Lightweight text tasks, classification, and summarization where cost matters more than frontier-level quality.. 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.
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
$0.39/1M in
$0.97/1M out
Speed
Fast
4/5 speed
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
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.
Gemma 2 9B costs $0.03 per million input tokens and $0.09 per million output tokens on the API. A month of 10M input and 2M output tokens runs about $0.48 at list price, before any batch or caching discounts.
What is Gemma 2 9B best for?
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 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 Gemma 2 9B?
GPT-5.1-Codex-Max (OpenAI) at $1.25/1M/1M input against Gemma 2 9B's $0.03/1M/1M. The strongest choice for serious software engineering work, provided you can absorb the output-side pricing. Compare it first if Gemma 2 9B's pricing is the thing stopping you.
What is a faster alternative to Gemma 2 9B?
Gemma 4 26B A4B — fast against Gemma 2 9B's very fast, with 262k tokens of context. Worth the swap when response time is what your users notice rather than the last few points of reasoning depth.
Newsletter
Get notified when 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.