ZMIME
Comparison · 3 models · Updated Oct 4, 2026

GPT-5.6 Terra vs Qwen3.8 Max vs Kimi K3

Too close to call on our weighted score (Qwen3.8 Max 69, GPT-5.6 Terra 68, Kimi K3 65). The right pick depends on what you value most.

  1. OpenAI

    GPT-5.6 Terra

    Released Jul 9, 2026

    68/100
    • ECI159.8
    • Price$2.00 / $12.00
    • Context1.05M
  2. Alibaba (Qwen)

    Qwen3.8 Max

    Released Aug 3, 2026

    69/100
    • ECI156.6
    • Price$2.00 / $6.00
    • Context1M
  3. Moonshot AI

    Kimi K3

    Released Jul 16, 2026

    65/100
    • ECI157.6
    • Price$3.00 / $15.00
    • Context1.05M
01 — Verdict

Too close to call

It is close. Our weighted score puts them within 1 points (Qwen3.8 Max 69/100, GPT-5.6 Terra 68/100, Kimi K3 65/100), so choose by what matters most for your work: GPT-5.6 Terra for raw capability and Qwen3.8 Max on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGPT-5.6 TerraCapabilities Index (ECI): GPT-5.6 Terra 159.8 · Kimi K3 157.6 · Qwen3.8 Max 156.6
  • Lowest priceQwen3.8 MaxQwen3.8 Max $3.00 · GPT-5.6 Terra $4.50 · Kimi K3 $6.00 per 1M tokens (3:1 blend)
  • Longest contextGPT-5.6 Terra and Kimi K3GPT-5.6 Terra 1,050,000 · Kimi K3 1,048,576 · Qwen3.8 Max 1,000,000 tokens
  • Widest inputsQwen3.8 MaxGPT-5.6 Terra: Text, Images, PDFs · Qwen3.8 Max: Text, Images, PDFs, Video · Kimi K3: Text, Images, Video
  • Self-hostingKimi K3Publishes downloadable weights
How the score is built
MeasureWeightGPT-5.6 TerraQwen3.8 MaxKimi K3
CapabilityCapabilities Index (ECI)50%908688
Price25%192713
Inputs & features15%809080
Context window10%616061
Overall100%68/10069/10065/100
02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

GPT-5.6 Terra vs Qwen3.8 Max vs Kimi K3 specifications side by side
SpecificationGPT-5.6 TerraOpenAIQwen3.8 MaxAlibaba (Qwen)Kimi K3Moonshot AI
Capability
Capabilities Index (ECI)159.8 (best)156.6157.6
ECI rank#9 of 148 (best)#20 of 148#13 of 148
GPQA DiamondGraduate-level science questions93.3% (best)92.7%93.1%
FrontierMath Tiers 1–3Research-level mathematics86.0% (best)74.7%72.2%
OTIS Mock AIME 2024–2025Competition mathematics99.7% (best)99.4%97.2%
SimpleQA VerifiedShort factual questions43.2%45.8%50.6% (best)
Price per million tokens
Input$2.00 (best)$2.00 (best)$3.00
Output$12.00$6.00 (best)$15.00
Cached input$0.20 (best)$0.25$0.30
Blended (3:1)$4.50$3.00 (best)$6.00
Long-context rateOver 272K: $4.00 / $18.00Same rateSame rate
Price sourceOfficial OpenAI APIOfficial Alibaba APIOfficial Moonshot AI API
Limits
Context window1,050,000 tokens (best)1,000,000 tokens1,048,576 tokens
Max output128,000 tokens131,072 tokens (best)131,072 tokens (best)
Inputs and features
TextYesYesYes
ImagesYesYesYes
PDFsYesYesNo
AudioNoNoNo
VideoNoYesYes
ReasoningYeslow · medium · high · xhigh · maxYeslow · medium · xhighYeslow · high · max
Tool callingYesYesYes
Structured outputYesYesYes
Availability
WeightsProprietaryProprietaryOpen
API model IDgpt-5.6-terraqwen3.8-maxkimi-k3
API providers382568 (best)
ReleasedJul 9, 2026Aug 3, 2026Jul 16, 2026
Knowledge cutoffFeb 16, 2026——
03 — Cost

What would a month cost?

Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.

  • GPT-5.6 Terra$44.00
  • Qwen3.8 Max$32.00
  • Kimi K3$60.00
04 — Questions

Which should you choose?

Which is better: GPT-5.6 Terra, Qwen3.8 Max or Kimi K3?

It is close. Our weighted score puts them within 1 points (Qwen3.8 Max 69/100, GPT-5.6 Terra 68/100, Kimi K3 65/100), so choose by what matters most for your work: GPT-5.6 Terra for raw capability and Qwen3.8 Max on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, GPT-5.6 Terra, Qwen3.8 Max or Kimi K3?

Qwen3.8 Max is cheaper at $2.00 input / $6.00 output per million tokens (official Alibaba API price). GPT-5.6 Terra costs $2.00 input / $12.00 output per million tokens (official OpenAI API price); Kimi K3 costs $3.00 input / $15.00 output per million tokens (official Moonshot AI API price). At a typical mix of three input tokens to one output token, that is $3.00 per million tokens for Qwen3.8 Max versus $4.50 for GPT-5.6 Terra (1.5× as much) and $6.00 for Kimi K3 (2× as much).

Which scores higher on benchmarks?

GPT-5.6 Terra scores higher on the Capabilities Index (ECI): GPT-5.6 Terra 159.8 (#9 of 148), Kimi K3 157.6 (#13 of 148) and Qwen3.8 Max 156.6 (#20 of 148). The confidence ranges of the top two overlap (157.1–162.8 vs 154.9–160.4), so treat the gap as small. On individual benchmarks: GPQA Diamond — GPT-5.6 Terra 93.3%, Kimi K3 93.1%, Qwen3.8 Max 92.7%; FrontierMath Tiers 1–3 — GPT-5.6 Terra 86.0%, Qwen3.8 Max 74.7%, Kimi K3 72.2%; OTIS Mock AIME 2024–2025 — GPT-5.6 Terra 99.7%, Qwen3.8 Max 99.4%, Kimi K3 97.2%; SimpleQA Verified — Kimi K3 50.6%, Qwen3.8 Max 45.8%, GPT-5.6 Terra 43.2%.

Which is better for coding?

There are no published SWE-bench Verified results for GPT-5.6 Terra, Qwen3.8 Max and Kimi K3 yet, so there is no like-for-like coding score. On overall capability, GPT-5.6 Terra leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.

Which has the bigger context window?

GPT-5.6 Terra and Kimi K3 have the largest context windows (1,050,000 and 1,048,576 tokens), against 1,000,000 for Qwen3.8 Max. Maximum output per response: GPT-5.6 Terra up to 128,000, Qwen3.8 Max up to 131,072, Kimi K3 up to 131,072 tokens.

Which can read images, PDFs, audio or video?

GPT-5.6 Terra accepts text, images and PDFs; Qwen3.8 Max accepts text, images, PDFs and video; Kimi K3 accepts text, images and video. Qwen3.8 Max handles the widest range of inputs.

Are any of these open source?

Kimi K3 publishes its weights and can be self-hosted; GPT-5.6 Terra and Qwen3.8 Max is proprietary.

Which is newer?

Qwen3.8 Max is the newest, released Aug 3, 2026. Kimi K3 came out Jul 16, 2026; GPT-5.6 Terra came out Jul 9, 2026. Knowledge cutoff: GPT-5.6 Terra Feb 16, 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 Oct 4, 2026.