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Saba vs Moondream 3 Preview

Updated October 21, 2026. 0 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

SabaMistral AI
Coding
No data
Overall
6.5
Output $/M
$0.60
M Moondream 3 PreviewMoondream
Coding
No data
Overall
No data
Output $/M
$2.50
vs $0.60 vs $2.50 per 1M output tokens. Saba is 4.2x cheaper.

Decision reading

Neither model has a coding score yet, so the two cannot be ranked on coding.

Saba has the edge where output tokens cost 4.2x less, and where the context window is larger, 33K against 32K tokens.

Shared results
0
Saba only
4
Moondream 3 Preview only
0
Like-for-like categories
0 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
Saba not benchmarked, Moondream 3 Preview not benchmarked.
Widest category
No category has a result for both models.
Widest single gap
No benchmark has a result for both models.
Output price
Saba $0.60 against Moondream 3 Preview $2.50 per million output tokens, 4.2x apart.
Context window
Saba takes 33K tokens, Moondream 3 Preview 32K.

Benchmark by benchmark

First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.

CodingNot comparableSix of these boards feed the Vibe Coding Index0 boards, none shared
Coding benchmarks for Saba and Moondream 3 Preview
BenchmarkSabaMoondream 3 PreviewLeader
Neither model has a result on 38 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Intelligence benchmarks for Saba and Moondream 3 Preview
BenchmarkSabaMoondream 3 PreviewLeader
AA Intelligence Index6.5Not measuredOnly Saba measured
Neither model has a result on the other 1 board here
Agentic workNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Agentic work benchmarks for Saba and Moondream 3 Preview
BenchmarkSabaMoondream 3 PreviewLeader
Neither model has a result on 39 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Reasoning benchmarks for Saba and Moondream 3 Preview
BenchmarkSabaMoondream 3 PreviewLeader
GPQA Diamond (Artificial Analysis run)42.4%Not measuredOnly Saba measured
Humanity's Last Exam (Artificial Analysis run)4.3%Not measuredOnly Saba measured
Neither model has a result on the other 19 boards here
MathNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Math benchmarks for Saba and Moondream 3 Preview
BenchmarkSabaMoondream 3 PreviewLeader
Neither model has a result on 13 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Knowledge benchmarks for Saba and Moondream 3 Preview
BenchmarkSabaMoondream 3 PreviewLeader
MMLU Pro (Artificial Analysis run)61.1%Not measuredOnly Saba measured
Neither model has a result on the other 16 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for Saba and Moondream 3 Preview
BenchmarkSabaMoondream 3 PreviewLeader
Neither model has a result on 9 boards here
GeneralNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
General benchmarks for Saba and Moondream 3 Preview
BenchmarkSabaMoondream 3 PreviewLeader
Neither model has a result on 46 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Saba and Moondream 3 Preview
BenchmarkSabaMoondream 3 PreviewLeader
Neither model has a result on 5 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

Saba$0.0005Fits in one request
Moondream 3 Preview$0.0015Fits in one request

Saba costs less

Repository review

50K input + 3K output tokens

Saba$0.012Exceeds the context window
Moondream 3 Preview$0.022Exceeds the context window

Saba costs less

Agent loop

200K input + 10K output tokens

Saba$0.046Exceeds the context window
Moondream 3 Preview$0.085Exceeds the context window

Saba costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of Saba and Moondream 3 Preview
SpecificationMistral SabaMoondream 3 Preview
MakerMistral AIMoondream
WeightsNo public weights listedOpen weights
ReleasedFebruary 17, 2025October 15, 2026
Context window33K32K
Input $/Mtok$0.20$0.30
Output $/Mtok$0.60$2.50
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Saba better than Moondream 3 Preview for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Saba has the edge where output tokens cost 4.2x less, and where the context window is larger, 33K against 32K tokens.

Which is cheaper, Saba or Moondream 3 Preview?

Saba costs $0.20 per million input tokens and $0.60 per million output tokens; Moondream 3 Preview costs $0.30 and $2.50. Cost per solved task is known for neither of them.

Which has the bigger context window, Saba or Moondream 3 Preview?

Saba, with 33K tokens against 32K.

How many benchmarks is the Saba vs Moondream 3 Preview comparison based on?

0 benchmarks have a result for both models as of October 21, 2026. Saba's coding index rests on 0 independent benchmarks and Moondream 3 Preview's on 0. Where only one model has a result, the page says so instead of naming a winner.

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