Olmo 3 32B Think vs DeepSeek V4.1 Flash
At a Glance
| Compare |  DeepSeek V4.1 FlashDeepSeek | |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| CostLower is better · Published-token output estimate | UnrankedNot in the 44-model eligible cohort | #5 of 44$0.022 per LiveBench case |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.15Openrouter ↗ · Aug 28, 2026 | $0.15DeepSeek ↗ · Sep 10, 2026 |
| Output priceFrom · USD / 1M tokens | $0.50Openrouter ↗ · Aug 28, 2026 | $0.60Deepinfra ↗ · Sep 22, 2026 |
| Context windowMaximum documented tokens | 66K | 1,049K |
| Model facts checked | Aug 28, 2026View model evidence → | Sep 10, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
Side-by-Side Facts
| Field | Olmo-3-32B-Think | DeepSeek-V4.1-Flash |
|---|---|---|
| Developer | Ai2 | DeepSeek |
| Family | Olmo 3 32b Think | Deepseek V4 1 |
| Model | Olmo-3-32B-Think | DeepSeek-V4.1-Flash |
| Version | Olmo-3-32B-Think | DeepSeek-V4.1-Flash |
| Lifecycle | active | active |
| Released | Unknown | 2026-09-10 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text, Image |
| Output modalities | Text | Text |
| Context window | 66K | 1,049K |
| Total parameters | 32.2B | 763.2B |
| Active parameters | Unknown | Unknown |
| License | apache-2.0 | mit |
| Open weights | Yes | Yes |
| API available | Yes | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Openrouter (Standard) | DeepSeek (Standard), Deepinfra (Standard), Together Ai (Standard) |
| Capabilities | chat, generation, reasoning | agents, chat, fim, generation, reasoning, responses, structured_outputs, tools, vision |
| Architecture design | Unknown | Causal Encoder-Decoder (20 encoder + 20 decoder layers) |
| Backbone parameters | Unknown | 552000000000 parameters |
| Active parameters during decode | Unknown | 16000000000 parameters |
| Active parameters during prefill | Unknown | 8000000000 parameters |
| Pre-training corpus | Unknown | 45000000000000 tokens |
| Reasoning effort range | Unknown | 1–100 |
| Routed experts per MoE layer | Unknown | 384 experts |
| Routed experts per token | Unknown | 6 experts |
| Transformer layers | Unknown | 40 layers |
Olmo 3 32B Think Capabilities
DeepSeek V4.1 Flash Capabilities
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Primary Evidence
Sources and Freshness
Questions
Olmo 3 32B Think vs DeepSeek V4.1 Flash FAQs
Is Olmo 3 32B Think or DeepSeek V4.1 Flash better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Olmo 3 32B Think and DeepSeek V4.1 Flash, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Olmo 3 32B Think or DeepSeek V4.1 Flash?+
Olmo 3 32B Think is $0.15 and DeepSeek V4.1 Flash is $0.15 per million tokens, so they are tied on this metric. Olmo 3 32B Think is $0.50 and DeepSeek V4.1 Flash is $0.60 per million tokens, so Olmo 3 32B Think is cheaper on this metric.
Which has a larger context window, Olmo 3 32B Think or DeepSeek V4.1 Flash?+
DeepSeek V4.1 Flash has the larger sourced context window. Olmo 3 32B Think supports 66K and DeepSeek V4.1 Flash supports 1,049K.
Which performs better in benchmarks, Olmo 3 32B Think or DeepSeek V4.1 Flash?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Olmo 3 32B Think or DeepSeek V4.1 Flash be self-hosted?+
Both models have the same recorded self-hosting status: supported. Olmo 3 32B Think is open weight; DeepSeek V4.1 Flash is open weight.
Can Olmo 3 32B Think and DeepSeek V4.1 Flash understand images?+
Olmo 3 32B Think is not documented with image input; DeepSeek V4.1 Flash is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Olmo 3 32B Think or DeepSeek V4.1 Flash?+
DeepSeek V4.1 Flash has the larger sourced maximum output: Olmo 3 32B Think supports 33K and DeepSeek V4.1 Flash supports 393K output tokens.
Do Olmo 3 32B Think and DeepSeek V4.1 Flash support reasoning and tool use?+
Olmo 3 32B Think: reasoning. DeepSeek V4.1 Flash: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Olmo 3 32B Think or DeepSeek V4.1 Flash?+
Olmo 3 32B Think has 1 sourced provider route; DeepSeek V4.1 Flash has 3, so DeepSeek V4.1 Flash has broader tracked availability.
Which offers better value, Olmo 3 32B Think or DeepSeek V4.1 Flash?+
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.