o4-mini vs Kimi K2 Thinking
Too close to call on our weighted score (o4-mini 59, Kimi K2 Thinking 58). The right pick depends on what you value most.
OpenAIo4-mini
59/100- ECI145.6
- Price$1.10 / $4.40
- Context200K
Moonshot AIKimi K2 Thinking
58/100- ECI146.0
- Price$0.60 / $2.50
- Context262K
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Make it a three-way comparison.
Too close to call
It is close. Our weighted score puts them within 2 points (o4-mini 59/100, Kimi K2 Thinking 58/100), so choose by what matters most for your work: Kimi K2 Thinking for raw capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityKimi K2 ThinkingCapabilities Index (ECI): Kimi K2 Thinking 146.0 · o4-mini 145.6
- Lowest priceKimi K2 ThinkingKimi K2 Thinking $1.07 · o4-mini $1.93 per 1M tokens (3:1 blend)
- Longest contextKimi K2 ThinkingKimi K2 Thinking 262,144 · o4-mini 200,000 tokens
- Widest inputso4-minio4-mini: Text, Images · Kimi K2 Thinking: Text
- Self-hostingKimi K2 ThinkingPublishes downloadable weights
| Measure | Weight | o4-mini | Kimi K2 Thinking |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 73 | 73 |
| Price | 25% | 36 | 48 |
| Inputs & features | 15% | 70 | 35 |
| Context window | 10% | 32 | 37 |
| Overall | 100% | 59/100 | 58/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | o4-miniOpenAI | Kimi K2 ThinkingMoonshot AI |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 145.6 | 146.0 (best) |
| ECI rank | #76 of 148 | #72 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 79.6% | 84.2% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | 36.1% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 81.7% | 83.1% (best) |
| SimpleQA VerifiedShort factual questions | 19.6% | — |
| Price per million tokens | ||
| Input | $1.10 | $0.60 (best) |
| Output | $4.40 | $2.50 (best) |
| Cached input | $0.275 | — |
| Blended (3:1) | $1.93 | $1.07 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official OpenAI API | Median of 10 providers |
| Limits | ||
| Context window | 200,000 tokens | 262,144 tokens (best) |
| Max output | 100,000 tokens | 262,144 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | 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 | Open |
| API model ID | o4-mini | — |
| API providers | 19 (best) | 10 |
| Released | Apr 16, 2025 | Nov 6, 2025 |
| Knowledge cutoff | May 2024 | Aug 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- o4-mini$19.80
- Kimi K2 Thinking$11.00
Which should you choose?
Which is better: o4-mini or Kimi K2 Thinking?
It is close. Our weighted score puts them within 2 points (o4-mini 59/100, Kimi K2 Thinking 58/100), so choose by what matters most for your work: Kimi K2 Thinking for raw capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, o4-mini or Kimi K2 Thinking?
Kimi K2 Thinking is cheaper at $0.60 input / $2.50 output per million tokens (median across 10 API providers). o4-mini costs $1.10 input / $4.40 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $1.07 per million tokens for Kimi K2 Thinking versus $1.93 for o4-mini (1.8× as much).
Which scores higher on benchmarks?
Kimi K2 Thinking scores higher on the Capabilities Index (ECI): Kimi K2 Thinking 146.0 (#72 of 148) and o4-mini 145.6 (#76 of 148). The confidence ranges of the top two overlap (143.4–147.6 vs 143.0–147.4), so treat the gap as small. On individual benchmarks: GPQA Diamond — Kimi K2 Thinking 84.2%, o4-mini 79.6%; OTIS Mock AIME 2024–2025 — Kimi K2 Thinking 83.1%, o4-mini 81.7%.
Which is better for coding?
There are no published SWE-bench Verified results for o4-mini and Kimi K2 Thinking yet, so there is no like-for-like coding score. On overall capability, Kimi K2 Thinking leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.
Which has the bigger context window?
Kimi K2 Thinking has the largest context window at 262,144 tokens, against 200,000 for o4-mini. Maximum output per response: o4-mini up to 100,000, Kimi K2 Thinking up to 262,144 tokens.
Which can read images, PDFs, audio or video?
o4-mini accepts text and images; Kimi K2 Thinking accepts text. o4-mini handles the widest range of inputs.
Are any of these open source?
Kimi K2 Thinking publishes its weights and can be self-hosted; o4-mini is proprietary.
Which is newer?
Kimi K2 Thinking is the newest, released Nov 6, 2025. o4-mini came out Apr 16, 2025. Knowledge cutoff: o4-mini May 2024, Kimi K2 Thinking Aug 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 Oct 4, 2026.
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