Olmo 3.1 32B Instruct vs Gemma 4 26B A4B
Benchmark Performance
Available Benchmarks
| Benchmark | Olmo-3.1-32B-Instruct | Gemma 4 26B-A4B |
|---|---|---|
| LMArena Text Arenatext-2026-09-01-011508720696 · arena_rating · leader | 1,311.9091% of row best · rating · olmo-3.1-32b-instruct; 95% CI [1305.73447366, 1318.07100374]; votes 11463; rank 223 | 1,434.86100% of row best · rating · gemma-4-26b-a4b; 95% CI [1427.26766156, 1442.45594559]; votes 5814; rank 78 |
| Overall ResultCounted from the protocol-matched rows above | 0 benchmark wins | 1 benchmark winOverall lead |
Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.
Technical Differences
Side-by-Side Facts
| Field | Olmo-3.1-32B-Instruct | Gemma 4 26B-A4B |
|---|---|---|
| Developer | Ai2 | Google DeepMind |
| Family | Olmo 3 1 32b Instruct | Gemma 4 |
| Model | Olmo-3.1-32B-Instruct | Gemma 4 26B-A4B |
| Version | Olmo-3.1-32B-Instruct | Gemma 4 26B-A4B |
| Lifecycle | active | active |
| Released | Unknown | 2026-03-11 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text, Image |
| Output modalities | Text | Text |
| Context window | 66K | 262K |
| Total parameters | 32.2B | 26B |
| Active parameters | Unknown | 4B |
| License | apache-2.0 | apache-2.0 |
| Open weights | Yes | Yes |
| API available | Unknown | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Unknown | Deepinfra (Standard), Google Gemini (Standard), Openrouter (Standard), Together Ai (Standard) |
| Capabilities | chat, generation, tools | chat, generation, reasoning, structured_outputs, tools |
13 comparable fields · 8 material differences · Pair passes the primary-source comparison gate
Olmo 3.1 32B Instruct Capabilities
Gemma 4 26B A4B Capabilities
Internal Comparison Graph
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Primary Evidence
Sources and Freshness
Questions
Olmo 3.1 32B Instruct vs Gemma 4 26B A4B FAQs
Is Olmo 3.1 32B Instruct or Gemma 4 26B A4B better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Olmo 3.1 32B Instruct and Gemma 4 26B A4B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Olmo 3.1 32B Instruct or Gemma 4 26B A4B?+
Only Gemma 4 26B A4B has a directly sourced input price: $0.070 per million tokens. Only Gemma 4 26B A4B has a directly sourced output price: $0.34 per million tokens.
Which has a larger context window, Olmo 3.1 32B Instruct or Gemma 4 26B A4B?+
Gemma 4 26B A4B has the larger sourced context window. Olmo 3.1 32B Instruct supports 66K and Gemma 4 26B A4B supports 262K.
Which performs better in benchmarks, Olmo 3.1 32B Instruct or Gemma 4 26B A4B?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Olmo 3.1 32B Instruct or Gemma 4 26B A4B be self-hosted?+
Both models have the same recorded self-hosting status: supported. Olmo 3.1 32B Instruct is open weight; Gemma 4 26B A4B is open weight.
Can Olmo 3.1 32B Instruct and Gemma 4 26B A4B understand images?+
Olmo 3.1 32B Instruct is not documented with image input; Gemma 4 26B A4B is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Olmo 3.1 32B Instruct or Gemma 4 26B A4B?+
Neither has a larger sourced maximum output. Olmo 3.1 32B Instruct is 33K and Gemma 4 26B A4B is —.
Do Olmo 3.1 32B Instruct and Gemma 4 26B A4B support reasoning and tool use?+
Olmo 3.1 32B Instruct: tool calling. Gemma 4 26B A4B: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Olmo 3.1 32B Instruct or Gemma 4 26B A4B?+
Olmo 3.1 32B Instruct has 0 sourced provider routes; Gemma 4 26B A4B has 4, so Gemma 4 26B A4B has broader tracked availability.
Which offers better value, Olmo 3.1 32B Instruct or Gemma 4 26B A4B?+
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.