Flint vs Mercury 3 vs Kimi K3.1 Pro
Kimi K3.1 Pro comes out ahead, 72 to 51 and 36 on our weighted score, though Mercury 3 is 25× cheaper per token.
Recursive
Flint
36/100- ECI—
- Price—
- Context262K
InceptionMercury 3
51/100- ECI—
- Price$0.10 / $0.35
- Context1M
- Our pick
Moonshot AIKimi K3.1 Pro
72/100- ECI—
- Price$2.00 / $10.00
- Context1.05M
Kimi K3.1 Pro is our pick
Kimi K3.1 Pro is the better all-round choice, scoring 72/100 against Mercury 3 (51) and Flint (36). It leads on inputs & features. The score weighs inputs & features 60%, context window 40%. 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 3Mercury 3 $0.163 · Kimi K3.1 Pro $4.00 per 1M tokens (3:1 blend) · Flint unpriced
- Longest contextKimi K3.1 ProKimi K3.1 Pro 1,048,576 · Mercury 3 1,000,000 · Flint 262,144 tokens
- Widest inputsKimi K3.1 ProFlint: Text · Mercury 3: Text · Kimi K3.1 Pro: Text, Images, Video
- Self-hostingFlintPublishes downloadable weights (Apache-2.0)
| Measure | Weight | Flint | Mercury 3 | Kimi K3.1 Pro |
|---|---|---|---|---|
| Inputs & features | 60% | 35 | 45 | 80 |
| Context window | 40% | 37 | 60 | 61 |
| Overall | 100% | 36/100 | 51/100 | 72/100 |
Left out because at least one model lacks the data: capability and price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | FlintRecursive | Mercury 3Inception | Kimi K3.1 ProMoonshot AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | — | $0.10 (best) | $2.00 |
| Output | — | $0.35 (best) | $10.00 |
| Cached input | — | $0.01 (best) | $0.20 |
| Blended (3:1) | — | $0.163 (best) | $4.00 |
| Long-context rate | — | Same rate | Same rate |
| Price source | — | Official Inception API | Official Moonshot AI API |
| Limits | |||
| Context window | 262,144 tokens | 1,000,000 tokens | 1,048,576 tokens (best) |
| Max output | 262,144 tokens (best) | 131,072 tokens | 131,072 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | Yes |
| Reasoning | Yes | Yeslow · medium · high | Yeslow · high · max |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | Yes |
| Availability | |||
| Weights | OpenApache-2.0 | Proprietary | Proprietary |
| API model ID | — | mercury-3 | kimi-k3.1-pro |
| API providers | 1 | 3 | 17 (best) |
| Released | Oct 21, 2026 | Oct 16, 2026 | Oct 23, 2026 |
| Knowledge cutoff | Jun 2026 | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Flint—
- Mercury 3$1.70
- Kimi K3.1 Pro$40.00
Which should you choose?
Which is better: Flint, Mercury 3 or Kimi K3.1 Pro?
Kimi K3.1 Pro is the better all-round choice, scoring 72/100 against Mercury 3 (51) and Flint (36). It leads on inputs & features. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Flint, Mercury 3 or Kimi K3.1 Pro?
Mercury 3 is cheaper at $0.10 input / $0.35 output per million tokens (official Inception API price). Kimi K3.1 Pro costs $2.00 input / $10.00 output per million tokens (official Moonshot AI API price). At a typical mix of three input tokens to one output token, that is $0.163 per million tokens for Mercury 3 versus $4.00 for Kimi K3.1 Pro (25× as much). Flint has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Flint has not been scored yet, Mercury 3 has not been scored yet and Kimi K3.1 Pro has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Flint, Mercury 3 and Kimi K3.1 Pro yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
Kimi K3.1 Pro has the largest context window at 1,048,576 tokens, against 1,000,000 for Mercury 3 and 262,144 for Flint. Maximum output per response: Flint up to 262,144, Mercury 3 up to 131,072, Kimi K3.1 Pro up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Flint accepts text; Mercury 3 accepts text; Kimi K3.1 Pro accepts text, images and video. Kimi K3.1 Pro handles the widest range of inputs.
Are any of these open source?
Flint publishes its weights (Apache-2.0) and can be self-hosted; Mercury 3 and Kimi K3.1 Pro is proprietary.
Which is newer?
Kimi K3.1 Pro is the newest, released Oct 23, 2026. Flint came out Oct 21, 2026; Mercury 3 came out Oct 16, 2026. Knowledge cutoff: Flint Jun 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.
