Mercury 2 vs Aion-3.0
Mercury 2 comes out ahead, 52 to 26 on our weighted score, and it is the cheaper option too.
Mercury 2 is our pick
Mercury 2 is the better all-round choice, scoring 52/100 against Aion-3.0 (26). It leads on price and inputs & features. 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 priceMercury 2Mercury 2 $0.375 · Aion-3.0 $3.75 per 1M tokens (3:1 blend)
- Longest contextAion-3.0Aion-3.0 131,072 · Mercury 2 128,000 tokens
- Widest inputsSame inputsMercury 2: Text · Aion-3.0: Text
- Self-hostingNo open weightsBoth are available only through APIs
| Measure | Weight | Mercury 2 | Aion-3.0 |
|---|---|---|---|
| Price | 50% | 67 | 22 |
| Inputs & features | 30% | 45 | 35 |
| Context window | 20% | 24 | 25 |
| Overall | 100% | 52/100 | 26/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification |  Mercury 2Inception | Aion-3.0Aion Labs |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.25 (best) | $3.00 |
| Output | $0.75 (best) | $6.00 |
| Cached input | $0.025 | — |
| Blended (3:1) | $0.375 (best) | $3.75 |
| Long-context rate | Same rate | Same rate |
| Price source | Official Inception API | Median of 4 providers |
| Limits | ||
| Context window | 128,000 tokens | 131,072 tokens (best) |
| Max output | 50,000 tokens (best) | 32,768 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yeslow · medium · high | Yes |
| Tool calling | Yes | Yes |
| Structured output | Yes | No |
| Availability | ||
| Weights | Proprietary | Proprietary |
| API model ID | mercury-2 | — |
| API providers | 7 (best) | 4 |
| Released | Feb 24, 2026 | May 5, 2026 |
| Knowledge cutoff | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Mercury 2$4.00
- Aion-3.0$42.00
Which should you choose?
Which is better: Mercury 2 or Aion-3.0?
Mercury 2 is the better all-round choice, scoring 52/100 against Aion-3.0 (26). It leads on price and inputs & features. 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, Mercury 2 or Aion-3.0?
Mercury 2 is cheaper at $0.25 input / $0.75 output per million tokens (official Inception API price). Aion-3.0 costs $3.00 input / $6.00 output per million tokens (median across 4 API providers). At a typical mix of three input tokens to one output token, that is $0.375 per million tokens for Mercury 2 versus $3.75 for Aion-3.0 (10× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Mercury 2 has not been scored yet and Aion-3.0 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Mercury 2 and Aion-3.0 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
Aion-3.0 has the largest context window at 131,072 tokens, against 128,000 for Mercury 2. Maximum output per response: Mercury 2 up to 50,000, Aion-3.0 up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Mercury 2 accepts text; Aion-3.0 accepts text. They handle the same number of input types.
Are any of these open source?
No. Mercury 2 and Aion-3.0 are proprietary and only available through APIs and apps.
Which is newer?
Aion-3.0 is the newest, released May 5, 2026. Mercury 2 came out Feb 24, 2026.
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.
