API cost decision in 10 seconds

NewPerceptron Mk1 vs Olmo 3 32B Think

Pick Olmo 3 32B Think when budget and context both matter.

Pricing data updated: 2026-05-26T11:08:00Z Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick Olmo 3 32B Think when budget and context both matter.

On the standard 1M input plus 500K output workload, Olmo 3 32B Think is estimated at $0.4 vs $0.9 for Perceptron Mk1, saving $0.5 (55.6% lower).

Cost-first pickOlmo 3 32B Think

Context-first pickOlmo 3 32B Think

Sample savings$0.555.6%

10x traffic gap$5

Olmo 3 32B Think is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $5. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Olmo 3 32B Think stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shape	Token mix	Better pick	Perceptron Mk1	Olmo 3 32B Think
Input-heavy / RAG	5M input + 500K output	Olmo 3 32B Think	$1.5	$1
Balanced workload	1M input + 1M output	Olmo 3 32B Think	$1.65	$0.65
Output-heavy chatbot	1M input + 5M output	Olmo 3 32B Think	$7.65	$2.65

Cheaper input Tie $0.15 vs $0.15 / 1M

Both models report the same input price at $0.15 per 1M tokens.

Cheaper output Olmo 3 32B Think $1.5 vs $0.5 / 1M

Olmo 3 32B Think is $1 cheaper per 1M output tokens (66.7% lower; 3x difference).

Larger context Olmo 3 32B Think 32.77K vs 65.54K

Olmo 3 32B Think has 32.77K more context (2x larger).

Sample workload Olmo 3 32B Think $0.9 vs $0.4

Olmo 3 32B Think is $0.5 cheaper on the standard workload (55.6% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.

Monthly input tokens Monthly output tokens

Perceptron Mk1 Calculating… Estimated API cost

Olmo 3 32B Think Calculating… Estimated API cost

Cheaper for this workload Calculating… Difference: calculating…

This estimate uses normalized public API pricing per 1M tokens. It is a planning aid, not a billing quote. Verify provider pricing, limits, and terms before production use.

Quick Decision

Verdict

both models tie on input price; Olmo 3 32B Think has the lower output price; Olmo 3 32B Think offers the larger context window. For the 1M input plus 500K output sample, Olmo 3 32B Think is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $0.9 for Perceptron Mk1 and $0.4 for Olmo 3 32B Think.

Best Fit

Choose Perceptron Mk1 when its provider, model quality, latency, or availability is more important than the numeric price/context winner.

Choose Olmo 3 32B Think when you care most about lower output-token price, and larger context window.

Decision Notes

On the standard 1M input plus 500K output workload, Olmo 3 32B Think is estimated at $0.4 vs $0.9 for Perceptron Mk1, saving $0.5 (55.6% lower).
Olmo 3 32B Think is $0.5 cheaper on the standard workload (55.6% lower).
Both models report the same input price at $0.15 per 1M tokens.
Olmo 3 32B Think is $1 cheaper per 1M output tokens (66.7% lower; 3x difference).
Olmo 3 32B Think has 32.77K more context (2x larger).

Head-to-Head Specs

Feature	NewPerceptron Mk1 (Perceptron)	Olmo 3 32B Think (AllenAI)
Input Price prompt tokens per 1M	$0.15	$0.15
Completion Price per 1M tokens	$1.5	$0.5
Sample Workload Cost 1M input + 500K output	$0.9	$0.4
Context Window	32.77K	65.54K
Release Date	2026-05-12	2025-11-21

Use-Case Decision Matrix

Use case	Better pick	Why
Budget-constrained production	Olmo 3 32B Think	On the standard 1M input plus 500K output workload, Olmo 3 32B Think is estimated at $0.4 vs $0.9 for Perceptron Mk1, saving $0.5 (55.6% lower).
High-volume input processing	Tie	Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbots	Olmo 3 32B Think	Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document work	Olmo 3 32B Think	A larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Same-provider lower-cost swaps

No lower-cost same-provider swap is currently tracked for this pair.

Larger context near this budget

Llama 4 Scout offers 10M context with $0.23 sample workload cost.
Owl Alpha offers 1.05M context with $0 sample workload cost.
Gemini 3.1 Flash Lite offers 1.05M context with $1 sample workload cost.
DeepSeek V4 Pro offers 1.05M context with $0.87 sample workload cost.

Popular competitors

No popular competitor is currently available.

Cheaper alternatives

Review low-cost models sorted by a standard 1M input plus 500K output workload.

Open cheapest models

Larger context alternatives

Find models with larger context windows for RAG, long documents, and codebase review.

Open largest context models

Provider catalogs

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Perceptron catalog

Review all tracked Perceptron models before deciding whether this matchup is the right shortlist.

Open Perceptron models

AllenAI catalog

Check other AllenAI models with comparable pricing, context, or release timing.

Open AllenAI models

Perceptron Mk1

Perceptron Mk1 (Mark One) is Perceptron's highest-quality vision-language model for video and embodied reasoning.** It accepts image and video inputs paired with natural language queries, and produces detailed visual understanding...

Olmo 3 32B Think

Olmo 3 32B Think is a large-scale, 32-billion-parameter model purpose-built for deep reasoning, complex logic chains and advanced instruction-following scenarios. Its capacity enables strong performance on demanding evaluation tasks and...