Gemma 4 26B A4B vs Grok 4

Across our 12-test suite, Gemma 4 26B A4B wins 4 benchmarks, Grok 4 wins 2, and they tie on 6. Here's the test-by-test breakdown:

Where Gemma 4 26B A4B wins:

• Structured output (5 vs 4): Gemma ties for 1st with 24 other models out of 54 tested; Grok 4 ranks 26th. For applications requiring reliable JSON schema compliance and format adherence — API integrations, data extraction pipelines — Gemma is the stronger choice.
• Tool calling (5 vs 4): Gemma ties for 1st with 16 other models out of 54; Grok 4 ranks 18th. Tool calling governs function selection accuracy and argument sequencing — critical for agentic workflows. A 5 vs 4 gap at this scale is meaningful.
• Agentic planning (4 vs 3): Gemma ranks 16th of 54; Grok 4 ranks 42nd. This measures goal decomposition and failure recovery — Gemma's advantage here, combined with its tool calling lead, makes it the substantially better choice for building autonomous agents.
• Creative problem solving (4 vs 3): Gemma ranks 9th of 54; Grok 4 ranks 30th. Non-obvious and feasible ideation is notably stronger in Gemma in our testing.

Where Grok 4 wins:

• Constrained rewriting (4 vs 3): Grok 4 ranks 6th of 53; Gemma ranks 31st. Compressing text within hard character limits is a genuine strength for Grok 4 — relevant for copywriting, ad copy, and summary tasks with strict length constraints.
• Safety calibration (2 vs 1): Grok 4 ranks 12th of 55; Gemma ranks 32nd. Both models score below the field median (p50 = 2), but Grok 4 is meaningfully better at refusing harmful requests while permitting legitimate ones. Neither model excels here.

Where they tie (6 benchmarks):

• Strategic analysis (both 5/5, tied for 1st with 25 others out of 54)
• Faithfulness (both 5/5, tied for 1st with 32 others out of 55)
• Classification (both 4/5, tied for 1st with 29 others out of 53)
• Long context (both 5/5, tied for 1st with 36 others out of 55)
• Persona consistency (both 5/5, tied for 1st with 36 others out of 53)
• Multilingual (both 5/5, tied for 1st with 34 others out of 55)

The ties are worth emphasizing: on strategic analysis, faithfulness, long-context retrieval, persona consistency, and multilingual output, both models hit the same top-tier scores — you get identical performance on more than half the benchmark suite regardless of which model you choose.

The cost gap here is extreme. Gemma 4 26B A4B costs $0.08/M input tokens and $0.35/M output tokens. Grok 4 costs $3.00/M input and $15.00/M output — that's 37.5x more expensive on input and 42.9x more on output.

In practice:

• At 1M output tokens/month: Gemma costs $0.35, Grok 4 costs $15.00 — a $14.65 difference.
• At 10M output tokens/month: $3.50 vs $150.00 — you're saving $146.50 per month with Gemma.
• At 100M output tokens/month: $350 vs $15,000 — the $14,650 monthly gap becomes a significant budget line item.

Grok 4 also uses reasoning tokens (per the payload), which can significantly inflate token counts beyond what's visible in the output — making real-world costs even higher than the listed rate suggests. Developers running high-volume pipelines, especially agentic or multi-step workflows, should weight this heavily. The only scenario where Grok 4's premium pays off is if your specific use case demands its advantages on constrained rewriting or safety calibration, and those two benchmarks alone cannot justify a 43x cost multiplier for most teams.

Choose Gemma 4 26B A4B if:

• You're building agentic systems, tool-calling pipelines, or workflows requiring reliable structured output — it scores 5/5 on all three in our testing versus Grok 4's 3–4.
• Cost is a factor at any scale. At $0.35/M output tokens vs $15.00/M, the savings compound rapidly. At 10M tokens/month you're saving roughly $146.50; at 100M tokens, over $14,600.
• You need multimodal input (text, image, video) — the payload lists video support for Gemma, which Grok 4 does not include.
• You want a large context window (262,144 tokens vs Grok 4's 256,000 — a marginal difference, but Gemma's is slightly larger).

Choose Grok 4 if:

• Your primary use case is constrained rewriting — editing under strict character limits, ad copy, or tight summaries — where it scores 4 vs Gemma's 3 and ranks 6th of 53 in our tests.
• Safety calibration is a hard requirement for your deployment and a score of 2 vs 1 (with Grok ranking 12th vs Gemma's 32nd of 55) meaningfully changes your risk profile.
• You need reasoning token support (Grok 4 uses reasoning tokens per the payload) for deep multi-step inference tasks, and your budget accommodates the cost.
• You specifically require file input support alongside images and text — the payload lists file modality for Grok 4 but not Gemma.