AI Model Comparison

Gemma 4 26B A4B vs Qwen3 Coder Next

Verdict
Gemma 4 26B A4B vs Qwen3 Coder Next: Qwen3 Coder Next scores higher on the Intelligence Index

Head-to-head specifications

MetricGemma 4 26B A4BQwen3 Coder NextDifference
Intelligence Index25.026.0-3.8%
Coding Index39.336.2+8.6%
Agentic Index11.08.8
Context window400K tokens400K tokens
Blended price ($/1M tokens)$0.13$0.40-67.5%
Output speed (tokens/s)5494-42.6%
AccessOpen weightsOpen weights
  • Qwen3 Coder Next leads overall capability (Intelligence Index 26.0 vs 25.0).
  • Gemma 4 26B A4B is the cheaper model to run at $0.13/1M blended tokens — about 3.1× cheaper.

Verdict: Gemma 4 26B A4B or Qwen3 Coder Next?

Our recommendation
Gemma 4 26B A4B is the clearly stronger overall choice, winning most of the dimensions that matter.

Gemma 4 26B A4B advantages

  • Coding ability (+8%)
  • Agentic task performance (+20%)
  • Affordability (+68%)

Qwen3 Coder Next advantages

  • Output speed (+43%)

Which should you choose?

  • Choose the Gemma 4 26B A4B if coding and software development are your main workload.
  • Choose the Qwen3 Coder Next if low latency and fast generation matter for your application.
  • Choose the Gemma 4 26B A4B if you build agents or multi-step tool-use workflows.

Value for money

Gemma 4 26B A4B offers more intelligence per dollar (3.0× 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 Qwen3 Coder Next: 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).

Qwen3 Coder Next — Alibaba text model with an Intelligence Index of 26, a 400K-token context window and a blended price of $0.4/1M tokens (open weights).

Gemma 4 26B A4B vs Qwen3 Coder Next: Qwen3 Coder Next scores higher on the Intelligence Index. Qwen3 Coder Next leads overall capability (Intelligence Index 26.0 vs 25.0). Gemma 4 26B A4B is the cheaper model to run at $0.13/1M blended tokens — about 3.1× cheaper.

Capability: intelligence, coding and agentic work

On the composite Intelligence Index the Qwen3 Coder Next scores 26.0 versus 25.0. For software development, the Coding Index puts Gemma 4 26B A4B ahead (39.3 vs 36.2). On agentic, multi-step tool-use tasks, Gemma 4 26B A4B measures stronger. Composite indices summarize many evaluations, but always test on your own workload before committing.

Context window and speed

The Gemma 4 26B A4B accepts up to 400K tokens per request, which sets how much documentation, transcript or code it can reason over at once. In measured throughput, Qwen3 Coder Next generates faster (94 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 $0.40 per 1M tokens). Gemma 4 26B A4B is open weights and Qwen3 Coder Next 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 Gemma 4 26B A4B better than the Qwen3 Coder Next?

Gemma 4 26B A4B is the clearly stronger overall choice, winning most of the dimensions that matter. Qwen3 Coder Next leads overall capability (Intelligence Index 26.0 vs 25.0).

What is the main difference between the Gemma 4 26B A4B and the Qwen3 Coder Next?

Qwen3 Coder Next leads overall capability (Intelligence Index 26.0 vs 25.0). Gemma 4 26B A4B is the cheaper model to run at $0.13/1M blended tokens — about 3.1× cheaper.

Which is better value?

Gemma 4 26B A4B offers more intelligence per dollar (3.0× 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 coding and software development are your main workload. Choose the Qwen3 Coder Next if low latency and fast generation matter for your application.

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.

ER
EquivalentTo Research
Data & Benchmarks Team

We compile published benchmark results (Cinebench 2024, Geekbench 6, AnTuTu v10, 3DMark), manufacturer specifications and market pricing from nine regions into normalized, comparable datasets. Every figure traces to a named public source listed on each page.

Benchmark leaderboard compilationMulti-market pricing normalizationUnit & currency conversion
✓ Reviewed by EquivalentTo Editorial Review, Data Quality & Methodology.
Last updated 2026-07-01
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