Claude Opus 4.5 vs Gemma 4 12B
Benchmark Performance
Available Benchmarks
Technical Differences
Side-by-Side Facts
| Field | Claude Opus 4.5 | Gemma 4 12B |
|---|---|---|
| Developer | Anthropic | Google Deepmind |
| Family | Claude 4 | Gemma 4 |
| Model | Claude Opus 4.5 | Gemma 4 12B |
| Version | Claude Opus 4.5 | Gemma 4 12B |
| Lifecycle | active | active |
| Released | 2025-11-24 | 2026-05-23 |
| Knowledge cutoff | 2025-05-01 | Unknown |
| Input modalities | Unknown | Text, Image, Video, Audio |
| Output modalities | Unknown | Text |
| Context window | 200,000 | 262,144 |
| Total parameters | Unknown | 12,000,000,000 |
| Active parameters | Unknown | Unknown |
| License | Unknown | apache-2.0 |
| Open weights | No | Yes |
| API available | Yes | Yes |
| Self-hostable | No | Yes |
| Provider access | Anthropic (Standard) | Together Ai (Standard) |
| Capabilities | chat, generation, reasoning, structured_outputs, tools | chat, generation, reasoning, structured_outputs, tools |
12 comparable fields · 9 material differences · Interactive comparison only; indexing gate not met
Claude Opus 4.5 Capabilities
Gemma 4 12B Capabilities
Internal Comparison Graph
Related Comparisons
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|---|---|---|---|
Gemma 4 12BGoogle Deepmind | vs | Gemma 4 E2BGoogle Deepmind | family variantsaudio, image, text, video |
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Gemma 4 12BGoogle Deepmind | vs | InklingThinking Machines Lab | cross-developer peersaudio, image, text, video |
Gemma 4 12BGoogle Deepmind | vs |  Muse Glimmer 30BMeta | cross-developer peersimage, text |
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Gemma 4 12BGoogle Deepmind | vs |  Ministral-3-14B-Instruct-2512Mistral AI | cross-developer peersimage, text |
 PaddleOCR-VL-1.5Baidu | vs | Gemma 4 12BGoogle Deepmind | cross-developer peersimage, text |
Gemma 4 12BGoogle Deepmind | vs | Ministral-3-14B-Base-2512Mistral AI | cross-developer peersimage, text |
| vs | Gemma 4 12BGoogle Deepmind | cross-developer peersimage, text | |
Gemma 4 12BGoogle Deepmind | vs | cross-developer peerstext | |
Gemma 4 12BGoogle Deepmind | vs | cross-developer peerstext |
Primary Evidence
Sources and Freshness
Questions
Claude Opus 4.5 vs Gemma 4 12B FAQs
Is Claude Opus 4.5 or Gemma 4 12B better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Claude Opus 4.5 and Gemma 4 12B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Claude Opus 4.5 or Gemma 4 12B?+
Neither model has a directly sourced input price in this comparison. Neither model has a directly sourced output price in this comparison.
Which has a larger context window, Claude Opus 4.5 or Gemma 4 12B?+
Gemma 4 12B has the larger sourced context window. Claude Opus 4.5 supports 200,000 and Gemma 4 12B supports 262,144.
Which performs better in benchmarks, Claude Opus 4.5 or Gemma 4 12B?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Claude Opus 4.5 or Gemma 4 12B be self-hosted?+
Gemma 4 12B is the only model in this pair currently marked as self-hostable. Claude Opus 4.5 is not marked open weight; Gemma 4 12B is open weight.
Can Claude Opus 4.5 and Gemma 4 12B understand images?+
Claude Opus 4.5 is not documented with image input; Gemma 4 12B is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Claude Opus 4.5 or Gemma 4 12B?+
Neither has a larger sourced maximum output. Claude Opus 4.5 is 64,000 and Gemma 4 12B is —.
Do Claude Opus 4.5 and Gemma 4 12B support reasoning and tool use?+
Claude Opus 4.5: reasoning and tool calling. Gemma 4 12B: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Claude Opus 4.5 or Gemma 4 12B?+
Claude Opus 4.5 has 1 sourced provider route; Gemma 4 12B has 1, a tie.
Which offers better value, Claude Opus 4.5 or Gemma 4 12B?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.