Olmo 3 7B Think vs Gemini 3.8 Flash Cyber
Benchmark Performance
Available Benchmarks
Technical Differences
Side-by-Side Facts
| Field | Olmo-3-7B-Think | Gemini 3.8 Flash Cyber |
|---|---|---|
| Developer | Ai2 | Google DeepMind |
| Family | Olmo 3 7b Think | Gemini 3 |
| Model | Olmo-3-7B-Think | Gemini 3.8 Flash Cyber |
| Version | Olmo-3-7B-Think | Gemini 3.8 Flash Cyber |
| Lifecycle | active | active |
| Released | Unknown | 2026-09-02 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text |
| Output modalities | Text | Text |
| Context window | 66K | Unknown |
| Total parameters | 7.3B | Unknown |
| Active parameters | Unknown | Unknown |
| License | apache-2.0 | Unknown |
| Open weights | Yes | No |
| API available | Unknown | No |
| Self-hostable | Yes | No |
| Provider access | Unknown | Unknown |
| Capabilities | chat, generation, reasoning | automated-patching, cybersecurity, reasoning, vulnerability-detection |
10 comparable fields · 7 material differences · Pair passes the primary-source comparison gate
Olmo 3 7B Think Capabilities
Gemini 3.8 Flash Cyber Capabilities
Internal Comparison Graph
Related Comparisons
| A | Pair | B | Context |
|---|---|---|---|
| vs |  GPT-6 AstraOpenAI | cross-developer peerstext | |
| vs | Claude Fable 5.1Anthropic | cross-developer peerstext | |
| vs | Gemini 3.1 ProGoogle DeepMind | cross-developer peerstext | |
| vs |  DeepSeek-V4-ProDeepSeek | cross-developer peerstext | |
| vs | Grok 4.6xAI | cross-developer peerstext | |
| vs |  Qwen3.8-MaxQwen | cross-developer peerstext | |
| vs |  Kimi-K3Moonshot AI | cross-developer peerstext | |
 MiniMax-M3MiniMax | vs | cross-developer peerstext | |
| vs |  GLM-5.3Z.ai | cross-developer peerstext | |
| vs |  Hy4 previewTencent | cross-developer peerstext | |
| vs | Seed 2.1 ProByteDance Seed | cross-developer peerstext | |
| vs |  Mistral Large 3Mistral AI | cross-developer peerstext |
Primary Evidence
Sources and Freshness
Questions
Olmo 3 7B Think vs Gemini 3.8 Flash Cyber FAQs
Is Olmo 3 7B Think or Gemini 3.8 Flash Cyber better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Olmo 3 7B Think and Gemini 3.8 Flash Cyber, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Olmo 3 7B Think or Gemini 3.8 Flash Cyber?+
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, Olmo 3 7B Think or Gemini 3.8 Flash Cyber?+
Neither model has a larger sourced context window in this comparison. Olmo 3 7B Think is 66K and Gemini 3.8 Flash Cyber is —.
Which performs better in benchmarks, Olmo 3 7B Think or Gemini 3.8 Flash Cyber?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Olmo 3 7B Think or Gemini 3.8 Flash Cyber be self-hosted?+
Olmo 3 7B Think is the only model in this pair currently marked as self-hostable. Olmo 3 7B Think is open weight; Gemini 3.8 Flash Cyber is not marked open weight.
Can Olmo 3 7B Think and Gemini 3.8 Flash Cyber understand images?+
Olmo 3 7B Think is not documented with image input; Gemini 3.8 Flash Cyber is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Olmo 3 7B Think or Gemini 3.8 Flash Cyber?+
Neither has a larger sourced maximum output. Olmo 3 7B Think is 33K and Gemini 3.8 Flash Cyber is —.
Do Olmo 3 7B Think and Gemini 3.8 Flash Cyber support reasoning and tool use?+
Olmo 3 7B Think: reasoning. Gemini 3.8 Flash Cyber: reasoning. Feature support does not establish relative quality.
Which is available from more inference providers, Olmo 3 7B Think or Gemini 3.8 Flash Cyber?+
Olmo 3 7B Think has 0 sourced provider routes; Gemini 3.8 Flash Cyber has 0, a tie.
Which offers better value, Olmo 3 7B Think or Gemini 3.8 Flash Cyber?+
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.