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Comparison · 3 models · Updated Nov 2, 2026

Aion-RP 1.0 (8B) vs Qwen2.5-VL 72B Instruct vs Saba

Too close to call on our weighted score (Saba 46, Qwen2.5-VL 72B Instruct 44, Aion-RP 1.0 (8B) 24). The right pick depends on what you value most.

  1. Aion Labs

    Aion-RP 1.0 (8B)

    Released Feb 4, 2025

    24/100
    • ECI—
    • Price$0.80 / $1.60
    • Context33K
  2. Alibaba (Qwen)

    Qwen2.5-VL 72B Instruct

    Released Jan 26, 2025

    44/100
    • ECI—
    • Price$0.905 / $1.00
    • Context131K
  3. Mistral AI

    Saba

    Released Feb 17, 2025

    46/100
    • ECI—
    • Price$0.20 / $0.60
    • Context33K
01 — Verdict

Too close to call

It is close. Our weighted score puts them within 2 points (Saba 46/100, Qwen2.5-VL 72B Instruct 44/100, Aion-RP 1.0 (8B) 24/100), so choose by what matters most for your work: Saba on price and Qwen2.5-VL 72B Instruct for long inputs. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

  • CapabilityNot enough dataNo independent benchmark covers every model here yet
  • Lowest priceSabaSaba $0.30 · Qwen2.5-VL 72B Instruct $0.93 · Aion-RP 1.0 (8B) $1.00 per 1M tokens (3:1 blend)
  • Longest contextQwen2.5-VL 72B InstructQwen2.5-VL 72B Instruct 131,072 · Aion-RP 1.0 (8B) 32,768 · Saba 32,768 tokens
  • Widest inputsQwen2.5-VL 72B Instruct and SabaAion-RP 1.0 (8B): Text · Qwen2.5-VL 72B Instruct: Text, Images · Saba: Text, PDFs
  • Self-hostingAion-RP 1.0 (8B) and Qwen2.5-VL 72B InstructPublishes downloadable weights
How the score is built
MeasureWeightAion-RP 1.0 (8B)Qwen2.5-VL 72B InstructSaba
Price50%484972
Inputs & features30%05035
Context window20%0250
Overall100%24/10044/10046/100

Left out because at least one model lacks the data: capability. The remaining weights were rescaled.

02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

Aion-RP 1.0 (8B) vs Qwen2.5-VL 72B Instruct vs Saba specifications side by side
SpecificationAion-RP 1.0 (8B)Aion LabsQwen2.5-VL 72B InstructAlibaba (Qwen)SabaMistral AI
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
Input$0.80$0.905$0.20 (best)
Output$1.60$1.00$0.60 (best)
Cached input———
Blended (3:1)$1.00$0.93$0.30 (best)
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 4 providersMedian of 6 providersMedian of 4 providers
Limits
Context window32,768 tokens131,072 tokens (best)32,768 tokens
Max output29,491 tokens (best)8,192 tokens26,214 tokens
Inputs and features
TextYesYesYes
ImagesNoYesNo
PDFsNoNoYes
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingNoYesYes
Structured outputNoNoNo
Availability
WeightsOpenOpenProprietary
API model ID———
API providers46 (best)4
ReleasedFeb 4, 2025Jan 26, 2025Feb 17, 2025
Knowledge cutoffDec 31, 2023Apr 2024Sep 30, 2024
03 — Cost

What would a month cost?

Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.

  • Aion-RP 1.0 (8B)$11.20
  • Qwen2.5-VL 72B Instruct$11.06
  • Saba$3.20
04 — Questions

Which should you choose?

Which is better: Aion-RP 1.0 (8B), Qwen2.5-VL 72B Instruct or Saba?

It is close. Our weighted score puts them within 2 points (Saba 46/100, Qwen2.5-VL 72B Instruct 44/100, Aion-RP 1.0 (8B) 24/100), so choose by what matters most for your work: Saba on price and Qwen2.5-VL 72B Instruct for long inputs. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

Which is cheaper, Aion-RP 1.0 (8B), Qwen2.5-VL 72B Instruct or Saba?

Saba is cheaper at $0.20 input / $0.60 output per million tokens (median across 4 API providers). Qwen2.5-VL 72B Instruct costs $0.905 input / $1.00 output per million tokens (median across 6 API providers); Aion-RP 1.0 (8B) costs $0.80 input / $1.60 output per million tokens (median across 4 API providers). At a typical mix of three input tokens to one output token, that is $0.30 per million tokens for Saba versus $0.93 for Qwen2.5-VL 72B Instruct (3.1× as much) and $1.00 for Aion-RP 1.0 (8B) (3.3× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. Aion-RP 1.0 (8B) has not been scored yet, Qwen2.5-VL 72B Instruct has not been scored yet and Saba has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Aion-RP 1.0 (8B), Qwen2.5-VL 72B Instruct and Saba yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Aion-RP 1.0 (8B) does not support tool calling, which most coding agents need.

Which has the bigger context window?

Qwen2.5-VL 72B Instruct has the largest context window at 131,072 tokens, against 32,768 for Aion-RP 1.0 (8B) and 32,768 for Saba. Maximum output per response: Aion-RP 1.0 (8B) up to 29,491, Qwen2.5-VL 72B Instruct up to 8,192, Saba up to 26,214 tokens.

Which can read images, PDFs, audio or video?

Aion-RP 1.0 (8B) accepts text; Qwen2.5-VL 72B Instruct accepts text and images; Saba accepts text and PDFs. Qwen2.5-VL 72B Instruct handles the widest range of inputs.

Are any of these open source?

Aion-RP 1.0 (8B) and Qwen2.5-VL 72B Instruct publishes its weights and can be self-hosted; Saba is proprietary.

Which is newer?

Saba is the newest, released Feb 17, 2025. Aion-RP 1.0 (8B) came out Feb 4, 2025; Qwen2.5-VL 72B Instruct came out Jan 26, 2025. Knowledge cutoff: Aion-RP 1.0 (8B) Dec 31, 2023, Qwen2.5-VL 72B Instruct Apr 2024, Saba Sep 30, 2024.

How do you decide the winner?

Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Nov 2, 2026.