GPT-3.5 Turbo Instruct vs Kimi K2 Thinking
GPT-3.5 Turbo Instruct costs 1.3x less per output token than Kimi K2 Thinking ($2.00 vs $2.50 per million). Updated October 21, 2026; 1 benchmarks have a result for both.
GPT-3.5 Turbo Instruct or Kimi K2 Thinking: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-3.5 Turbo Instruct for output tokens 1.3x cheaper ($2.00 vs $2.50 per million) and work measured by METR time horizons, where it leads.
- Shared results
- 1
- GPT-3.5 Turbo Instruct only
- 0
- Kimi K2 Thinking only
- 29
- Like-for-like categories
- 1 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Kimi K2 Thinking has a AA Intelligence Index result, 22.0.
Directional only
Reasoning
GPQA Diamond
No call
Only Kimi K2 Thinking has a GPQA Diamond result, 78.5%.
Directional only
Math
AIME
No call
Only Kimi K2 Thinking has a AIME result, 85.4%.
Directional only
Knowledge
MMLU Pro
No call
Only Kimi K2 Thinking has a MMLU Pro result, 81.1%.
Directional only
Web design
Design Arena: websites
No call
Only Kimi K2 Thinking has a Design Arena: websites result, 1113.
Directional only
Long documents
Listed context window
Kimi K2 Thinking
Kimi K2 Thinking takes 262K tokens against 4K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Kimi K2 Thinking
GPT-3.5 Turbo Instruct $0.0025, Kimi K2 Thinking $0.0019 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Kimi K2 Thinking has the number, $0.61.
Directional only
At a glance
- Coding index
- GPT-3.5 Turbo Instruct not benchmarked, Kimi K2 Thinking not benchmarked.
- Widest category
- Agentic work, 37.7 points apart on average over 1 shared benchmark.
- Widest single gap
- METR time horizons: GPT-3.5 Turbo Instruct 21.5% against Kimi K2 Thinking 59.2%, 37.7 points apart on a 0 to 100 scale.
- Output price
- GPT-3.5 Turbo Instruct $2.00 against Kimi K2 Thinking $2.50 per million output tokens, 1.3x apart.
- Context window
- GPT-3.5 Turbo Instruct takes 4K tokens, Kimi K2 Thinking 262K.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | GPT-3.5 Turbo Instruct | Bars | Kimi K2 Thinking | Ties |
|---|---|---|---|---|
| Agentic work | 0 | 1 | ||
| All shared boards | 0 | 1 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index8 boards, none shared
| Benchmark | GPT-3.5 Turbo Instruct | Kimi K2 Thinking | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 63.4% | Only Kimi K2 Thinking measured |
| LiveCodeBench (Vals AI) | Not measured | 63.1% | Only Kimi K2 Thinking measured |
| SWE-bench Verified (Vals AI) | Not measured | 60.2% | Only Kimi K2 Thinking measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 85.3% | Only Kimi K2 Thinking measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 31.1% | Only Kimi K2 Thinking measured |
| Terminal-Bench | Not measured | 35.7% | Only Kimi K2 Thinking measured |
| WeirdML | Not measured | 42.8% | Only Kimi K2 Thinking measured |
| ALE-Bench | Not measured | 597.5 | Only Kimi K2 Thinking measured |
| Neither model has a result on the other 31 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-3.5 Turbo Instruct | Kimi K2 Thinking | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 22.0 | Only Kimi K2 Thinking measured |
| Epoch Capabilities Index | Not measured | 145.8 | Only Kimi K2 Thinking measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-3.5 Turbo Instruct | Kimi K2 Thinking | Leader |
|---|---|---|---|
| τ²-Bench Telecom | Not measured | 93.0% | Only Kimi K2 Thinking measured |
| METR time horizons | 21.5% | 59.2% | Kimi K2 Thinking |
| Neither model has a result on the other 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | GPT-3.5 Turbo Instruct | Kimi K2 Thinking | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 78.5% | Only Kimi K2 Thinking measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 83.8% | Only Kimi K2 Thinking measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 23.8% | Only Kimi K2 Thinking measured |
| Neither model has a result on the other 19 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | GPT-3.5 Turbo Instruct | Kimi K2 Thinking | Leader |
|---|---|---|---|
| AIME | Not measured | 85.4% | Only Kimi K2 Thinking measured |
| MGSM (Vals AI) | Not measured | 90.2% | Only Kimi K2 Thinking measured |
| AA Math Index | Not measured | 94.7 | Only Kimi K2 Thinking measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 94.7% | Only Kimi K2 Thinking measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | GPT-3.5 Turbo Instruct | Kimi K2 Thinking | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 81.1% | Only Kimi K2 Thinking measured |
| LegalBench (Vals AI) | Not measured | 80.2% | Only Kimi K2 Thinking measured |
| CaseLaw (Vals AI) | Not measured | 65.7% | Only Kimi K2 Thinking measured |
| CorpFin (Vals AI) | Not measured | 60.6% | Only Kimi K2 Thinking measured |
| TaxEval (Vals AI) | Not measured | 71.7% | Only Kimi K2 Thinking measured |
| MedQA (Vals AI) | Not measured | 92.6% | Only Kimi K2 Thinking measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 84.8% | Only Kimi K2 Thinking measured |
| Neither model has a result on the other 11 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | GPT-3.5 Turbo Instruct | Kimi K2 Thinking | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1113 | Only Kimi K2 Thinking measured |
| Neither model has a result on the other 8 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | GPT-3.5 Turbo Instruct | Kimi K2 Thinking | Leader |
|---|---|---|---|
| IFBench | Not measured | 68.1% | Only Kimi K2 Thinking measured |
| Long context reasoning (AA-LCR) | Not measured | 72.0% | Only Kimi K2 Thinking measured |
| CL-bench | Not measured | 17.6% | Only Kimi K2 Thinking measured |
| Neither model has a result on the other 43 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-3.5 Turbo Instruct | Kimi K2 Thinking | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Kimi K2 Thinking costs less
Repository review
50K input + 3K output tokens
Kimi K2 Thinking costs less
Agent loop
200K input + 10K output tokens
Kimi K2 Thinking costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | OpenAI GPT-3.5 Turbo Instruct | MoonshotAI Kimi K2 Thinking |
|---|---|---|
| Maker | OpenAI | Moonshot AI |
| Weights | No public weights listed | Open weights |
| Released | September 28, 2023 | November 6, 2025 |
| Context window | 4K | 262K |
| Input $/Mtok | $1.50 | $0.60 |
| Output $/Mtok | $2.00 | $2.50 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | Not computable | $0.61 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-3.5 Turbo Instruct better than Kimi K2 Thinking for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-3.5 Turbo Instruct for output tokens 1.3x cheaper ($2.00 vs $2.50 per million) and work measured by METR time horizons, where it leads.
Which is cheaper, GPT-3.5 Turbo Instruct or Kimi K2 Thinking?
GPT-3.5 Turbo Instruct costs $1.50 per million input tokens and $2.00 per million output tokens; Kimi K2 Thinking costs $0.60 and $2.50. Cost per solved task is known for Kimi K2 Thinking only.
Which has the bigger context window, GPT-3.5 Turbo Instruct or Kimi K2 Thinking?
Kimi K2 Thinking, with 262K tokens against 4K.
How many benchmarks is the GPT-3.5 Turbo Instruct vs Kimi K2 Thinking comparison based on?
1 benchmarks have a result for both models as of October 21, 2026. GPT-3.5 Turbo Instruct's coding index rests on 0 independent benchmarks and Kimi K2 Thinking's on 1. Where only one model has a result, the page says so instead of naming a winner.