Claude 4.1 Opus vs Gemma 4 12B
Head-to-head specifications
| Metric | Claude 4.1 Opus | Gemma 4 12B | Difference |
|---|---|---|---|
| Intelligence Index | 30.0 | 26.0 | +15.4% |
| Context window | 262K tokens | 400K tokens | — |
| Blended price ($/1M tokens) | $1.68 | $0.12 | +1,300.0% |
| Output speed (tokens/s) | 30 | 110 | -72.7% |
| Access | Proprietary API | Open weights | — |
- Claude 4.1 Opus leads overall capability (Intelligence Index 30.0 vs 26.0).
- Gemma 4 12B is the cheaper model to run at $0.12/1M blended tokens — about 14.0× cheaper.
- Gemma 4 12B offers the larger context window (400K tokens), useful for long documents and codebases.
Verdict: Claude 4.1 Opus or Gemma 4 12B?
Claude 4.1 Opus advantages
- General intelligence (+13%)
Gemma 4 12B advantages
- Context window (+35%)
- Affordability (+93%)
- Output speed (+73%)
Which should you choose?
- Choose the Claude 4.1 Opus if you need the strongest overall reasoning and accuracy.
- Choose the Gemma 4 12B if you work with long documents or large codebases.
Value for money
Gemma 4 12B offers more intelligence per dollar (12.1× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use. It is also open-weight, so self-hosting can reduce costs further at scale.
Claude 4.1 Opus vs Gemma 4 12B: which should you choose?
Claude 4.1 Opus — Anthropic multimodal model with an Intelligence Index of 30, a 262K-token context window and a blended price of $1.68/1M tokens.
Gemma 4 12B — Google text model with an Intelligence Index of 26, a 400K-token context window and a blended price of $0.12/1M tokens (open weights).
Claude 4.1 Opus vs Gemma 4 12B: Claude 4.1 Opus scores higher on the Intelligence Index. Claude 4.1 Opus leads overall capability (Intelligence Index 30.0 vs 26.0). Gemma 4 12B is the cheaper model to run at $0.12/1M blended tokens — about 14.0× cheaper.
Capability: intelligence, coding and agentic work
On the composite Intelligence Index the Claude 4.1 Opus scores 30.0 versus 26.0. Composite indices summarize many evaluations, but always test on your own workload before committing.
Context window and speed
The Gemma 4 12B accepts up to 400K tokens per request, which sets how much documentation, transcript or code it can reason over at once. In measured throughput, Gemma 4 12B generates faster (110 vs 30 tokens/s), which matters for interactive apps and high-volume pipelines.
Pricing and access
At blended per-token rates, Gemma 4 12B is the cheaper model to run ($0.12 vs $1.68 per 1M tokens). Claude 4.1 Opus is proprietary api and Gemma 4 12B is open weights. Open-weight models can be self-hosted, trading per-call cost for infrastructure you manage; for production also weigh rate limits, throughput and data-residency requirements.
The verdict
Both are credible choices in the ai model comparison space; the specification table above lays out every metric so you can weigh the trade-offs that matter to you. Pick the one whose strengths line up with how you will actually use it.
Frequently asked questions
Is the Claude 4.1 Opus better than the Gemma 4 12B?
Gemma 4 12B takes the overall edge, though Claude 4.1 Opus wins in specific areas worth weighing. Claude 4.1 Opus leads overall capability (Intelligence Index 30.0 vs 26.0).
What is the main difference between the Claude 4.1 Opus and the Gemma 4 12B?
Claude 4.1 Opus leads overall capability (Intelligence Index 30.0 vs 26.0). Gemma 4 12B is the cheaper model to run at $0.12/1M blended tokens — about 14.0× cheaper.
Which is better value?
Gemma 4 12B offers more intelligence per dollar (12.1× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use. It is also open-weight, so self-hosting can reduce costs further at scale.
Which should I choose?
Choose the Claude 4.1 Opus if you need the strongest overall reasoning and accuracy. Choose the Gemma 4 12B if you work with long documents or large codebases.
Methodology
Large language models are compared on independent leaderboard metrics: an Intelligence Index (a composite of reasoning and knowledge evaluations), Coding and Agentic indices where measured, community arena Elo, maximum context window, a blended API price per million tokens (weighted across cache-hit, input and output rates), and measured output speed in tokens per second. Where a model ships multiple reasoning-effort variants, we report its strongest variant. Benchmarks capture only part of real-world quality, which also depends on tool use, latency, safety and task fit — and this space moves quickly, so figures reflect the leaderboard snapshot on the page date.