MModelspectraIndependent AI Model Intelligence
Head-to-head · Updated 2026-09-08
中文
Model Comparison · Head to Head

GPT-6 Astra vs Kimi K3

GPT-6 Astra wins on Overall, Coding, Multimodal. Every numeric field is compared below, with a worked monthly-cost example and a pick rule for each use case.

VendorOpenAI / Moonshot AI
Data fields15+ dimensions
Updated2026-09-08
Read~9 min
01

Verdict at a glance

Bottom line: Choose GPT-6 Astra when coding depth matter most; choose Kimi K3 when lower cost, lower latency is the priority.

Choose GPT-6 Astra if you…

  • Best-in-class computer use
  • Frontier research & reasoning
  • Autonomous long-horizon tasks
  • Strongest cybersecurity (gated)
  • Best for: Computer use, Deep research, Cybersecurity

Choose Kimi K3 if you…

  • Best-in-class long text
  • Open-source and self-hostable
  • Strong codebase understanding
  • Fair price
  • Best for: Long-document reading, Codebase analysis, Chinese
02

Head-to-head aggregate scores

Scores are 0–100, aggregated from public benchmark information and independently weighted across three leaderboards. Rank is out of 26 tracked models.

GPT-6 Astra Higher overall
OpenAI · #1 overall
Overall96
Coding97
Multimodal90
VS
Kimi K3
Moonshot AI · #10 overall
Overall77
Coding71
Multimodal81

Aggregated from public sources and independently weighted; methodology on the Terms page. Scores within 3 points are treated as statistically tied.

03

Specs & pricing — every field side by side

List API prices in USD per 1M tokens. The highlighted cell is the stronger value/capability on that row.

DimensionGPT-6 AstraKimi K3Verdict
VendorOpenAI (US)Moonshot AI (CN)Different vendors
Released2026.092026.06GPT-6 Astra is newer
Overall (rank)96 · #177 · #10GPT-6 Astra +19
Coding97 · #371 · #15GPT-6 Astra +26
Multimodal90 · #781 · #13GPT-6 Astra +9
Context window1.05M256KGPT-6 Astra larger
Max output128K64KKimi K3 longer
Effective-context9699Kimi K3 more reliable
Input $/1M$10$3Kimi K3 cheaper
Output $/1M$50$15Kimi K3 cheaper
Cache discount50% offcustomGPT-6 Astra deeper
Speed~35 tok/s~45 tok/sKimi K3 faster
TTFT1.1s0.7sKimi K3 snappier
Function calling9480GPT-6 Astra ahead
Refusal rate~13%~6%Kimi K3 less restrictive
English9975GPT-6 Astra
Chinese7292Kimi K3
Modalitiestext, imagetext, imageSame
Open weightsNoYesKimi K3 is open
Fine-tuningNoNo
Free tierNo free API tier; Fast mode delivers up to ~2x throughputKimi App free; free quota on the open platform
SOC2 / no-trainyes / yesno / yes
Private deploymentNoYesKimi K3

Fields drawn from vendor public documentation and the Modelspectra 26-model dataset; speed varies with network, concurrency and prompt length. Verify current pricing before purchase.

04

Dimension-by-dimension analysis

Reasoning & overall intelligence

GPT-6 Astra leads the overall aggregate by 19 points (96 vs 77). That is a meaningful, not marginal, edge on hard, multi-step reasoning, while Kimi K3 remains a strong generalist that is not out of its depth on routine work.

Agentic coding

This is a decisive gap: GPT-6 Astra scores 97 against 71. On multi-file edits, SWE-style tickets and long-horizon agent loops GPT-6 Astra needs fewer correction turns; Kimi K3 is still competent for scripts and assisted completion but trails as task complexity rises.

Multimodal

GPT-6 Astra leads multimodal 90 vs 81. Neither emits native video, so the comparison is about parsing images and documents, not generation.

Speed & latency

Kimi K3 is faster in interactive use: ~45 tok/s with 0.7s TTFT versus ~35 tok/s with 1.1s TTFT (about 1.3× the throughput). For conversational UIs where perceived responsiveness drives retention, that edge is a real product factor even when raw reasoning is lower.

Context: window vs usable recall

Nominal windows are 1.05M for GPT-6 Astra and 256K for Kimi K3. Crucially, the larger nominal window does not win on usable recall: GPT-6 Astra advertises 1.05M but Kimi K3 scores higher on effective-context (99 vs 96), i.e. it actually retains more of what it was given.

Price & total cost

Kimi K3 is the cheaper API at $3/$15 versus GPT-6 Astra at $10/$50 per 1M input/output tokens — list input is about 3.3× lower. Cache discounts (GPT-6 Astra 50%) shift the effective bill, worked out below.

Chinese vs English

English: GPT-6 Astra 99 vs Kimi K3 75. Chinese: 72 vs 92. For Chinese-language production, Kimi K3 is the stronger pick. Note that non-Chinese models generally require overseas network access for their APIs.

Tool use & ecosystem

Function-calling score: GPT-6 Astra 94 vs Kimi K3 80, so GPT-6 Astra has the edge on structured tool use. Neither offers standard fine-tuning. Factor in existing SDK/plugin familiarity — switching cost often outweighs a few-point tool-use gap.

05

Cost worked example — same workload, real token math

Assume a production workload of 100M input + 30M output tokens per month, with 90% of input tokens served from cache. Figures use public list prices.

Scenario · per monthGPT-6 AstraKimi K3Gap
List priceno cache applied$2,500100M in × $10  +  30M out × $50$750100M in × $3  +  30M out × $153.33×gap
With caching90% of inputs cache-hit$2,05090M cached in × $5  +  10M in × $10  +  30M out × $50$750no published cache discount2.73×gap

Illustrative model; your input/output mix and cache-hit ratio change the result. Prices are list rates before any enterprise agreement.

06

Decision tree

IF the workload is agentic or multi-file coding and a wrong first pass is expensive  →  choose GPT-6 Astra (coding 97 vs 71).
IF you serve real-time users and latency is a product KPI  →  choose Kimi K3 (~45 tok/s, 0.7s TTFT).
IF you are cost-driven at scale on routine, high-volume workloads  →  choose Kimi K3 ($$3/$$15 per 1M in/out).
IF long-document recall has to be near-perfect  →  choose Kimi K3 (effective context 99 vs 96).
07

Frequently asked questions

Is GPT-6 Astra worth the higher price over Kimi K3?
At list the input rate is 3.3x higher, but cache discounts and output pricing narrow the effective gap. Pay the premium when GPT-6 Astra's stronger dimensions protect revenue; for routine volume Kimi K3 is the economical pick.
Which is better for agentic coding?
GPT-6 Astra is decisively stronger for coding (97 vs 71 on the aggregate). The gap shows on SWE-style multi-file tasks and long agent loops that need fewer correction turns; Kimi K3 is fine for routine scripts.
Does GPT-6 Astra's higher refusal rate matter in production?
GPT-6 Astra refuses about 13% of prompts versus 6% for Kimi K3. In unattended pipelines that means more retries, fallbacks and manual review, raising effective cost and latency even when the token price is lower.
How do costs compare at 100M tokens/month with caching?
At 100M input + 30M output with 90% of inputs cache-hit, GPT-6 Astra is about $2,050/month and Kimi K3 about $750/month after cache discounts ($2,500 and $750 at list).
Does the bigger context window actually matter?
Nominal windows are GPT-6 Astra (1.05M) and Kimi K3 (256K), but usable recall follows the effective-context score (96 vs 99). Prefer the higher effective-context model for long-document work where nothing can be missed.
How do they differ for Chinese-language and data-residency use?
Kimi K3 is the Chinese model (Chinese score 92, domestic cloud, possible private deployment) while GPT-6 Astra is the global model (Chinese 72, overseas API). Pick by language quality, access path and where data must reside.