Gemma 4 26B A4B vs GPT-5.4 Mini
Gemma 4 26B A4B is the stronger technical choice for most workloads — it wins on tool calling (5 vs 4 in our testing) and ties GPT-5.4 Mini on nine of twelve benchmarks, while costing roughly 13x less on output tokens ($0.35 vs $4.50 per million). GPT-5.4 Mini earns its premium only if safety calibration is a hard requirement, where it scores 2 vs Gemma's 1 in our tests, ranking 12th of 55 models compared to Gemma's 32nd. For the vast majority of API-driven applications, Gemma 4 26B A4B delivers equivalent or better benchmark results at a fraction of the cost.
Gemma 4 26B A4B
Benchmark Scores
External Benchmarks
Pricing
Input
$0.080/MTok
Output
$0.350/MTok
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openai
GPT-5.4 Mini
Benchmark Scores
External Benchmarks
Pricing
Input
$0.750/MTok
Output
$4.50/MTok
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Benchmark Analysis
Neither model has been assigned an aggregate bench_avg_score in our data, so this analysis is drawn from individual test scores across our 12-benchmark suite.
Where Gemma 4 26B A4B wins:
- Tool calling (5 vs 4): Gemma scores a 5 — tied for 1st with 16 other models out of 54 tested. GPT-5.4 Mini scores 4, ranking 18th of 54. For agentic workflows where function selection and argument accuracy matter, this is a meaningful edge.
Where GPT-5.4 Mini wins:
- Constrained rewriting (4 vs 3): GPT-5.4 Mini scores 4, ranking 6th of 53. Gemma scores 3, ranking 31st of 53. If your workload involves compressing text within hard character limits — ad copy, SMS, metadata — GPT-5.4 Mini handles it more reliably in our testing.
- Safety calibration (2 vs 1): GPT-5.4 Mini scores 2, ranking 12th of 55. Gemma scores 1, ranking 32nd of 55. Both are below the field median of 2, but GPT-5.4 Mini is measurably better at refusing harmful requests while permitting legitimate ones.
Where they tie (nine tests):
- Structured output (5/5): Both tied for 1st with 24 other models — solid JSON schema compliance from either.
- Faithfulness (5/5): Both tied for 1st with 32 others — neither hallucinates beyond source material in our tests.
- Long context (5/5): Both tied for 1st with 36 others on retrieval accuracy at 30K+ tokens. Note that GPT-5.4 Mini has a 400K context window vs Gemma's 262K, though both score identically on our long-context test.
- Multilingual (5/5): Both tied for 1st with 34 others.
- Persona consistency (5/5): Both tied for 1st with 36 others.
- Strategic analysis (5/5): Both tied for 1st with 25 others.
- Classification (4/4): Both tied for 1st with 29 others.
- Creative problem solving (4/4): Both rank 9th of 54, tied with 20 others.
- Agentic planning (4/4): Both rank 16th of 54, tied with 25 others.
The overall picture: Gemma 4 26B A4B wins 1 test, GPT-5.4 Mini wins 2, and they tie on 9. The advantage is modest in scope but meaningful in context — Gemma's tool-calling edge matters for developers, while GPT-5.4 Mini's safety and constrained-rewriting edges matter for consumer-facing or editorially constrained products.
Pricing Analysis
The pricing gap here is substantial. Gemma 4 26B A4B costs $0.08/M input tokens and $0.35/M output tokens. GPT-5.4 Mini costs $0.75/M input and $4.50/M output — roughly 9x more on input and nearly 13x more on output.
At 1M output tokens/month: Gemma costs $0.35 vs GPT-5.4 Mini's $4.50 — a $4.15 difference, negligible for most budgets.
At 10M output tokens/month: Gemma runs $3.50 vs $45.00 — a $41.50/month gap that starts to matter for growing products.
At 100M output tokens/month: Gemma costs $350 vs $4,500 — a $4,150/month difference that is a genuine infrastructure budget decision.
Developers running high-throughput pipelines — summarization, classification at scale, agentic loops — should take the cost gap seriously. The benchmark data shows Gemma ties or beats GPT-5.4 Mini on 10 of 12 tests, meaning you are paying a 13x premium on output for two tests where GPT-5.4 Mini has an edge: constrained rewriting and safety calibration. If neither of those is central to your use case, Gemma 4 26B A4B is the clear economic choice.
Real-World Cost Comparison
Bottom Line
Choose Gemma 4 26B A4B if:
- You are building agentic or tool-heavy applications — it scores 5 vs 4 on tool calling in our tests.
- You process at scale (10M+ output tokens/month) and the $4,150/month cost difference at 100M tokens is material.
- Your workload is dominated by structured output, faithfulness, long-context retrieval, multilingual support, or strategic analysis — Gemma matches GPT-5.4 Mini on all of them.
- You accept a below-median safety calibration score (1/5, rank 32 of 55) and have your own content moderation layer.
Choose GPT-5.4 Mini if:
- Safety calibration is a hard product requirement — it scores 2 vs Gemma's 1, ranking 12th of 55 in our tests.
- Your primary task is constrained rewriting (ad copy, character-limited content) — GPT-5.4 Mini ranks 6th of 53 vs Gemma's 31st.
- You need a larger context window ceiling — GPT-5.4 Mini supports 400K vs Gemma's 262K, though both score equally on our long-context benchmark.
- You are on OpenAI's ecosystem and the integration simplicity justifies the 13x output cost premium.
How We Test
We test every model against our 12-benchmark suite covering tool calling, agentic planning, creative problem solving, safety calibration, and more. Each test is scored 1–5 by an LLM judge. Read our full methodology.