Kimi K2 Thinking Turbo vs Llama Guard 3 1B
Kimi K2 Thinking Turbo (2025) and Llama Guard 3 1B (2024) are compact production models from Moonshot AI and AI at Meta. Kimi K2 Thinking Turbo ships a 262k-token context window, while Llama Guard 3 1B ships a 128k-token context window. On pricing, Llama Guard 3 1B costs $0.10/1M input tokens versus $1.15/1M for the alternative. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Llama Guard 3 1B is ~1050% cheaper at $0.10/1M; pay for Kimi K2 Thinking Turbo only for long-context analysis.
Decision scorecard
Local evidence first| Signal | Kimi K2 Thinking Turbo | Llama Guard 3 1B |
|---|---|---|
| Best for | general production evaluation | general production evaluation |
| Decision fit | Long context | Long context and Classification |
| Context window | 262k | 128k |
| Cheapest output | $8/1M tokens | $0.10/1M tokens |
| Provider routes | 1 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Kimi K2 Thinking Turbo has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Local decision data tags Kimi K2 Thinking Turbo for Long context.
- Llama Guard 3 1B has the lower cheapest tracked output price at $0.10/1M tokens.
- Local decision data tags Llama Guard 3 1B for Long context and Classification.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Kimi K2 Thinking Turbo
$2,920
Cheapest tracked route/tier: Vercel AI Gateway
Llama Guard 3 1B
$105
Cheapest tracked route/tier: Fireworks AI
Estimated monthly gap: $2,815. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- No overlapping tracked provider route is sourced for Kimi K2 Thinking Turbo and Llama Guard 3 1B; plan for SDK, billing, or endpoint changes.
- Llama Guard 3 1B is $7.90/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- No overlapping tracked provider route is sourced for Llama Guard 3 1B and Kimi K2 Thinking Turbo; plan for SDK, billing, or endpoint changes.
- Kimi K2 Thinking Turbo is $7.90/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-11-06 | 2024-09-25 |
| Context window | 262k | 128k |
| Parameters | 1T (32B active) | 1B |
| Architecture | - | decoder only |
| License | MIT(OSI) | Llama 2 Community |
| Openness | Open source | Open weights |
| Commercial use | Commercial use allowed | Commercial use with conditions |
| Knowledge cutoff | - | 2023-12 |
Pricing and availability
| Pricing attribute | Kimi K2 Thinking Turbo | Llama Guard 3 1B |
|---|---|---|
| Input price | $1.15/1M tokens | $0.10/1M tokens |
| Output price | $8/1M tokens | $0.10/1M tokens |
| Providers |
Capabilities
| Capability | Kimi K2 Thinking Turbo | Llama Guard 3 1B |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | No | No |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint is close: both models cover the core production surface. That makes context budget, benchmark fit, and provider maturity more important than a simple checklist. If your application depends on one integration detail, verify it against the provider route you plan to use, not just the base model listing.
For cost, Kimi K2 Thinking Turbo lists $1.15/1M input and $8/1M output tokens on the cheapest tracked provider, while Llama Guard 3 1B lists $0.10/1M input and $0.10/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama Guard 3 1B lower by about $3.10 per million blended tokens. Availability is 1 providers versus 1, so concentration risk also matters.
Choose Kimi K2 Thinking Turbo when long-context analysis and larger context windows are central to the workload. Choose Llama Guard 3 1B when provider fit and lower input-token cost are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency.
FAQ
Which has a larger context window, Kimi K2 Thinking Turbo or Llama Guard 3 1B?
Kimi K2 Thinking Turbo supports 262k tokens, while Llama Guard 3 1B supports 128k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Kimi K2 Thinking Turbo or Llama Guard 3 1B?
Llama Guard 3 1B is cheaper on tracked token pricing. Kimi K2 Thinking Turbo costs $1.15/1M input and $8/1M output tokens. Llama Guard 3 1B costs $0.10/1M input and $0.10/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Kimi K2 Thinking Turbo or Llama Guard 3 1B open source?
Kimi K2 Thinking Turbo is listed under MIT. Llama Guard 3 1B is listed under Llama 2 Community. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Where can I run Kimi K2 Thinking Turbo and Llama Guard 3 1B?
Kimi K2 Thinking Turbo is available on Vercel AI Gateway. Llama Guard 3 1B is available on Fireworks AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Kimi K2 Thinking Turbo over Llama Guard 3 1B?
Llama Guard 3 1B is ~1050% cheaper at $0.10/1M; pay for Kimi K2 Thinking Turbo only for long-context analysis. If your workload also depends on long-context analysis, start with Kimi K2 Thinking Turbo; if it depends on provider fit, run the same evaluation with Llama Guard 3 1B.
Continue comparing
Last reviewed: 2026-06-04. Data sourced from public model cards and provider documentation.