Macaron V1 Tall vs CoBuddy
Macaron V1 Tall comes out ahead, 55 to 46 on our weighted score, though CoBuddy is 9% cheaper per token.
- Our pick
Mindlab
Macaron V1 Tall
55/100- ECI—
- Price$0.247 / $1.43
- Context262K
BaiduCoBuddy
46/100- ECI—
- Price$0.28 / $1.13
- Context131K
Add a model
Make it a three-way comparison.
Macaron V1 Tall is our pick
Macaron V1 Tall is the better all-round choice, scoring 55/100 against CoBuddy (46). It leads on inputs & features and context window. CoBuddy wins on price. 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 priceCoBuddyCoBuddy $0.492 · Macaron V1 Tall $0.543 per 1M tokens (3:1 blend)
- Longest contextMacaron V1 TallMacaron V1 Tall 262,144 · CoBuddy 131,072 tokens
- Widest inputsMacaron V1 TallMacaron V1 Tall: Text, Images · CoBuddy: Text
- Self-hostingMacaron V1 TallPublishes downloadable weights (MIT)
| Measure | Weight | Macaron V1 Tall | CoBuddy |
|---|---|---|---|
| Price | 50% | 60 | 62 |
| Inputs & features | 30% | 60 | 35 |
| Context window | 20% | 37 | 25 |
| Overall | 100% | 55/100 | 46/100 |
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 | Macaron V1 TallMindlab | CoBuddyBaidu |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.247 (best) | $0.28 |
| Output | $1.43 | $1.13 (best) |
| Cached input | — | — |
| Blended (3:1) | $0.543 | $0.492 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 1 providers | Median of 1 providers |
| Limits | ||
| Context window | 262,144 tokens (best) | 131,072 tokens |
| Max output | 32,768 tokens | 65,536 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yes | Yes |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | OpenMIT | Proprietary |
| API model ID | — | — |
| API providers | 1 | 1 |
| Released | Jul 21, 2026 | May 6, 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.
- Macaron V1 Tall$5.33
- CoBuddy$5.06
Which should you choose?
Which is better: Macaron V1 Tall or CoBuddy?
Macaron V1 Tall is the better all-round choice, scoring 55/100 against CoBuddy (46). It leads on inputs & features and context window. CoBuddy wins on price. 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, Macaron V1 Tall or CoBuddy?
CoBuddy is cheaper at $0.28 input / $1.13 output per million tokens (median across 1 API provider). Macaron V1 Tall costs $0.247 input / $1.43 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $0.492 per million tokens for CoBuddy versus $0.543 for Macaron V1 Tall (1.1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Macaron V1 Tall has not been scored yet and CoBuddy has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Macaron V1 Tall and CoBuddy 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?
Macaron V1 Tall has the largest context window at 262,144 tokens, against 131,072 for CoBuddy. Maximum output per response: Macaron V1 Tall up to 32,768, CoBuddy up to 65,536 tokens.
Which can read images, PDFs, audio or video?
Macaron V1 Tall accepts text and images; CoBuddy accepts text. Macaron V1 Tall handles the widest range of inputs.
Are any of these open source?
Macaron V1 Tall publishes its weights (MIT) and can be self-hosted; CoBuddy is proprietary.
Which is newer?
Macaron V1 Tall is the newest, released Jul 21, 2026. CoBuddy came out May 6, 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.
