Gemma 4 26B A4B vs Grok 3 mini Reasoning
Head-to-head specifications
| Metric | Gemma 4 26B A4B | Grok 3 mini Reasoning | Difference |
|---|---|---|---|
| Intelligence Index | 25.0 | 27.0 | -7.4% |
| Context window | 400K tokens | 1M tokens | — |
| Blended price ($/1M tokens) | $0.13 | $0.16 | -18.8% |
| Output speed (tokens/s) | 54 | 66 | -18.2% |
| Access | Open weights | Proprietary API | — |
- Grok 3 mini Reasoning leads overall capability (Intelligence Index 27.0 vs 25.0).
- Gemma 4 26B A4B is the cheaper model to run at $0.13/1M blended tokens — about 1.2× cheaper.
- Grok 3 mini Reasoning offers the larger context window (1M tokens), useful for long documents and codebases.
Verdict: Gemma 4 26B A4B or Grok 3 mini Reasoning?
Gemma 4 26B A4B advantages
- Affordability (+19%)
Grok 3 mini Reasoning advantages
- General intelligence (+7%)
- Context window (+60%)
- Output speed (+18%)
Which should you choose?
- Choose the Gemma 4 26B A4B if you want the lowest cost per token at scale.
- Choose the Grok 3 mini Reasoning if you need the strongest overall reasoning and accuracy.
Value for money
Gemma 4 26B A4B offers more intelligence per dollar (1.1× 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.
Gemma 4 26B A4B vs Grok 3 mini Reasoning: which should you choose?
Gemma 4 26B A4B — Google text model with an Intelligence Index of 25, a 400K-token context window and a blended price of $0.13/1M tokens (open weights).
Grok 3 mini Reasoning — xAI multimodal model with an Intelligence Index of 27, a 1M-token context window and a blended price of $0.16/1M tokens.
Gemma 4 26B A4B vs Grok 3 mini Reasoning: Grok 3 mini Reasoning scores higher on the Intelligence Index. Grok 3 mini Reasoning leads overall capability (Intelligence Index 27.0 vs 25.0). Gemma 4 26B A4B is the cheaper model to run at $0.13/1M blended tokens — about 1.2× cheaper.
Capability: intelligence, coding and agentic work
On the composite Intelligence Index the Grok 3 mini Reasoning scores 27.0 versus 25.0. Composite indices summarize many evaluations, but always test on your own workload before committing.
Context window and speed
The Grok 3 mini Reasoning accepts up to 1 million tokens per request, which sets how much documentation, transcript or code it can reason over at once. In measured throughput, Grok 3 mini Reasoning generates faster (66 vs 54 tokens/s), which matters for interactive apps and high-volume pipelines.
Pricing and access
At blended per-token rates, Gemma 4 26B A4B is the cheaper model to run ($0.13 vs $0.16 per 1M tokens). Gemma 4 26B A4B is open weights and Grok 3 mini Reasoning is proprietary api. 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 Gemma 4 26B A4B better than the Grok 3 mini Reasoning?
Grok 3 mini Reasoning takes the overall edge, though Gemma 4 26B A4B wins in specific areas worth weighing. Grok 3 mini Reasoning leads overall capability (Intelligence Index 27.0 vs 25.0).
What is the main difference between the Gemma 4 26B A4B and the Grok 3 mini Reasoning?
Grok 3 mini Reasoning leads overall capability (Intelligence Index 27.0 vs 25.0). Gemma 4 26B A4B is the cheaper model to run at $0.13/1M blended tokens — about 1.2× cheaper.
Which is better value?
Gemma 4 26B A4B offers more intelligence per dollar (1.1× 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 Gemma 4 26B A4B if you want the lowest cost per token at scale. Choose the Grok 3 mini Reasoning if you need the strongest overall reasoning and accuracy.
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.