vs
5:1
overall capability wins (0 ties across 6 scored). Kimi K2.7 Code leads overall.
- Reasoning4:0
- Specs1:1
Verdict
Kimi K2.7 Code edges reasoning & knowledge; Kimi Linear 48B A3B Instruct offers ~4.0x larger context (1.0M vs 262K).
- Kimi K2.7 Code edges reasoning & knowledge
- Kimi Linear 48B A3B Instruct offers ~4.0x larger context (1.0M vs 262K)
Cost for 1M in + 250K out
Illustrative chat workload at primary-provider list prices.
- Kimi K2.7 Code
- $1.95
- Kimi Linear 48B A3B Instruct
- -
Price per 1M tokens
Full comparison
Organization
Moonshot
Moonshot
Family
Kimi
Kimi
License
Modified MIT
MIT
Open weights
Yes
Yes
Release
Jun 12, 2026
Oct 30, 2025
Knowledge cutoff
-
-
API / provider
Moonshot
No primary API price listed
Modalities
text, image, video → text
text → text
Specs
Context window
262K
1.0M
Max output
33K
-
Parameters
1.0T (32B act.)
48B (3B act.)
Pricing
Input $/1M
$0.95
—
Output $/1M
$4
—
Blended $/1M (3∶1)
$1.71
-
Speed
tok/s
55
-
TTFT (s)
0.5
-
Reasoning
MMLU-Pro
—
—
GPQA Diamond
89.6
41.2
Humanity's Last Exam
35.0
2.5
AIME 2025
—
—
MATH-500
—
—
Humanity's Last Exam (with tools)
—
—
AA-Omniscience Accuracy
39.6
—
AA-LCR v1.1
79.3
28.0
CritPt
10.0
—
MMMU-Pro
—
—
IFBench
63.1
28.1
Chartography
—
—
Chartography (With Tools)
—
—
Coding
SWE-bench Verified
—
—
SWE-bench Pro
—
—
SWE-bench Multilingual
—
—
LiveCodeBench
—
—
Terminal-Bench 2.1
67.4
—
Aider Polyglot
—
—
Terminal-Bench 3
—
—
BigCodeBench
—
—
SciCode
47.8
—
CursorBench
49.7
—
SWE-Rebench
—
—
NL2Repo-Bench
—
—
DeepSWE
—
—
WebDev Arena
1,473
—
Terminal-Bench 4.0
—
—
CursorBench 4.0
—
—
FrontierCode v1.1 (Main)
—
—
Arena
LMArena Elo
—
—
| Metric | Kimi K2.7 Code | Kimi Linear 48B A3B Instruct | Delta |
|---|---|---|---|
| Identity | |||
| Organization | Moonshot | Moonshot | — |
| Family | Kimi | Kimi | — |
| License | Modified MIT | MIT | — |
| Open weights | Yes | Yes | — |
| Release | Jun 12, 2026 | Oct 30, 2025 | — |
| Knowledge cutoff | - | - | — |
| API / provider | Moonshot | No primary API price listed | — |
| Modalities | text, image, video → text | text → text | — |
| Specs | |||
| Context window | 262K | 1.0M | B +786K |
| Max output | 33K | - | — |
| Parameters | 1.0T (32B act.) | 48B (3B act.) | A +952 |
| Pricing | |||
| Input $/1M | $0.95 | — | — |
| Output $/1M | $4 | — | — |
| Blended $/1M (3∶1) | $1.71 | - | — |
| Speed | |||
| tok/s | 55 | - | — |
| TTFT (s) | 0.5 | - | — |
| Reasoning | |||
| MMLU-Pro | — | — | — |
| GPQA Diamond | 89.6 | 41.2 | A +48.4 pts |
| Humanity's Last Exam | 35.0 | 2.5 | A +32.5 pts |
| AIME 2025 | — | — | — |
| MATH-500 | — | — | — |
| Humanity's Last Exam (with tools) | — | — | — |
| AA-Omniscience Accuracy | 39.6 | — | — |
| AA-LCR v1.1 | 79.3 | 28.0 | A +51.3 pts |
| CritPt | 10.0 | — | — |
| MMMU-Pro | — | — | — |
| IFBench | 63.1 | 28.1 | A +35.0 pts |
| Chartography | — | — | — |
| Chartography (With Tools) | — | — | — |
| Coding | |||
| SWE-bench Verified | — | — | — |
| SWE-bench Pro | — | — | — |
| SWE-bench Multilingual | — | — | — |
| LiveCodeBench | — | — | — |
| Terminal-Bench 2.1 | 67.4 | — | — |
| Aider Polyglot | — | — | — |
| Terminal-Bench 3 | — | — | — |
| BigCodeBench | — | — | — |
| SciCode | 47.8 | — | — |
| CursorBench | 49.7 | — | — |
| SWE-Rebench | — | — | — |
| NL2Repo-Bench | — | — | — |
| DeepSWE | — | — | — |
| WebDev Arena | 1,473 | — | — |
| Terminal-Bench 4.0 | — | — | — |
| CursorBench 4.0 | — | — | — |
| FrontierCode v1.1 (Main) | — | — | — |
| Arena | |||
| LMArena Elo | — | — | — |
Kimi K2.7 Code
- Context
- 262K / 33K out
- Parameters
- 1.0T (32B act.)
- Price
- $0.95 / $4
- Speed
- 55 tok/s · 0.5s TTFT
- Modalities
- text, image, video → text
- License
- Modified MIT
Open-weight coding specialist (1T MoE / 32B active) with text/image/video input — long-horizon agentic software engineering at $0.95/$4; HighSpeed SKU is $1.90/$8 at ~180 tok/s.
Kimi Linear 48B A3B Instruct
- Context
- 1.0M
- Parameters
- 48B (3B act.)
- Price
- —
- Speed
- —
- Modalities
- text → text
- License
- MIT
Moonshot AI's hybrid linear-attention MoE (48B total / 3B active) pairing Kimi Delta Attention with sparse global attention for cheaper long-context (up to 1M token) inference; no hosted API yet.
Benchmark charts
Winner bars are emphasized. Per-benchmark deltas sit above each chart.