Knowledge
Like-for-like- Gemma 4 12B
- 40.4
- Supported · #138/181
- GPT-4.1 mini
- 35.8
- Supported · #159/181
- Basis
- BenchAlign lane · 5 vs 2 public rows
- Reading
- Gemma 4 12B leads · intervals overlap
Five or fewer confirmed AI changes, with original sources, on mornings when something changed.A free source-linked morning brief.
See the free Radar BriefUpdated September 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
Gemma 4 12B has the higher public score estimate, 46.64 versus 34.46, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
1 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
Share or export
Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.
Prompts that approach the documented context limit
GPT-4.1 mini
GPT-4.1 mini has the larger documented context window.
Confidence: documented
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Gemma 4 12B and GPT-4.1 mini are scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.
Confidence: limited
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Gemma 4 12B and GPT-4.1 mini are scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.
Confidence: limited
1K fresh input + 500 output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: rate-fallback
50K fresh input + 3K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
3 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.
Each row shows the public-lane category score for both models: the BenchAlign lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.
| Category | Gemma 4 12B | GPT-4.1 mini | Basis | Reading |
|---|---|---|---|---|
| Knowledge | 40.4Supported · #138/181 | 35.8Supported · #159/181 | Like-for-likeBenchAlign lane · 5 vs 2 public rows | Gemma 4 12B leads · intervals overlap |
| Agentic | 47.9Estimated · #81/151 | 35.2Estimated · #131/151 | Directional onlyBenchAlign lane · 0 vs 0 public rows | Directional only |
| Coding | 46.6Estimated · #97/183 | 37.1Estimated · #153/183 | Directional onlyBenchAlign lane · 1 vs 1 public rows | Directional only |
| Instruction following | 89.8#21/120 | 44.2#93/120 | Directional onlyProvisional lane · 0 vs 0 weighted rows | Directional only |
| Reasoning | 34.0Unranked · 4 rankable rows | 53.6Unranked · 2 rankable rows | Not comparableProvisional lane · 1 vs 0 weighted rows | Not comparable |
| Math | 57.6Unranked · 1 rankable row | 28.5Unranked · 1 rankable row | Not comparableProvisional lane · 1 vs 1 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | 26.1#44/48 | 46.5Unranked · 1 rankable row | Not comparableProvisional lane · 1 vs 0 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.
Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.
Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.
GPQA
Knowledge
Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.
1K fresh input + 500 output tokens
Gemma 4 12B has no comparable published API token rate.
50K fresh input + 3K output tokens
Gemma 4 12B has no comparable published API token rate.
200K cached + 20K fresh input + 10K output tokens
GPT-4.1 mini has no published cached-input rate, so cached tokens use its listed input rate. Gemma 4 12B has no comparable published API token rate.
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
Maximum documented context; output-token limits may be lower.
Gemma 4 12B
GPT-4.1 mini
1M
Gemma 4 12B
Not sourced
GPT-4.1 mini
Not sourced
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Gemma 4 12B
No comparable hosted API rate
GPT-4.1 mini
Not published
Gemma 4 12B
text, image, audio, video
Google Gemma 4 model documentationGPT-4.1 mini
Not sourced
Gemma 4 12B
GPT-4.1 mini
Not sourced
Gemma 4 12B
Open Weights · open weights
Google gemma-4-12B model cardGPT-4.1 mini
Not sourced
Gemma 4 12B
Reasoning
GPT-4.1 mini
Non-Reasoning
Gemma 4 12B
Open Weight
GPT-4.1 mini
Proprietary
Gemma 4 12B
Open Weight
GPT-4.1 mini
Proprietary
Gemma 4 12B
2026-06-03
GPT-4.1 mini
2025-04-14
Run the same representative tasks against both endpoints before changing production traffic.
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
GPQA
Gemma 4 12B leads this result
GPQA-D
Not directly comparable
MMLU-Pro
Not directly comparable
HLE w/o tools
Not directly comparable
MMMLU
Not directly comparable
MMLU
Not directly comparable
IFEval
Not directly comparable
Gemma 4 12B has the higher public score estimate, 46.64 versus 34.46, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.
Gemma 4 12B scores higher for coding on the public lane, 46.6 to 37.1. Gemma 4 12B and GPT-4.1 mini are scored on Estimated evidence for coding, so the reading is directional rather than like-for-like. BenchLM does not name a winner for coding from a directional reading; read the shared benchmark rows directly and test the models on the same task set.
Gemma 4 12B scores higher for agentic tasks on the public lane, 47.9 to 35.2. Gemma 4 12B and GPT-4.1 mini are scored on Estimated evidence for agentic tasks, so the reading is directional rather than like-for-like. BenchLM does not name a winner for agentic tasks from a directional reading; read the shared benchmark rows directly and test the models on the same task set.
Both models do not have comparable published API token rates, so this page does not name a universal price winner.
GPT-4.1 mini has the larger documented context window: 1M, compared with 256K.
Last updated September 4, 2026
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