GPT-5.4 vs Llama 3.2 90B Instruct
GPT-5.4 (2026) and Llama 3.2 90B Instruct (2025) are frontier reasoning models from OpenAI and AI at Meta. GPT-5.4 ships a 1.05m-token context window, while Llama 3.2 90B Instruct ships a 128k-token context window. On pricing, GPT-5.4 ranges from $2.50 to $5/1M input tokens by tier; Llama 3.2 90B Instruct costs $1.35/1M input tokens. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
GPT-5.4 fits 8x more tokens; pick it for long-context work and Llama 3.2 90B Instruct for tighter calls.
Decision scorecard
Local evidence first| Signal | GPT-5.4 | Llama 3.2 90B Instruct |
|---|---|---|
| Best for | reasoning-heavy apps, multimodal apps, and tool-calling agents | multimodal apps |
| Decision fit | Coding, RAG, and Agents | RAG, Long context, and Vision |
| Context window | 1.05m | 128k |
| Cheapest output | $15/1M tokens | $1.80/1M tokens |
| Provider routes | 3 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- GPT-5.4 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GPT-5.4 has broader tracked provider coverage for fallback and procurement flexibility.
- GPT-5.4 uniquely exposes Reasoning, Function calling, and Tool use in local model data.
- Local decision data tags GPT-5.4 for Coding, RAG, and Agents.
- Llama 3.2 90B Instruct has the lower cheapest tracked output price at $1.80/1M tokens.
- Local decision data tags Llama 3.2 90B Instruct for RAG, Long context, and Vision.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
GPT-5.4
$5,750
Cheapest tracked route/tier: OpenAI API
Llama 3.2 90B Instruct
$1,530
Cheapest tracked route/tier: AWS Bedrock
Estimated monthly gap: $4,220. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- No overlapping tracked provider route is sourced for GPT-5.4 and Llama 3.2 90B Instruct; plan for SDK, billing, or endpoint changes.
- Llama 3.2 90B Instruct is $13.20/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Reasoning, Function calling, and Tool use before moving production traffic.
- No overlapping tracked provider route is sourced for Llama 3.2 90B Instruct and GPT-5.4; plan for SDK, billing, or endpoint changes.
- GPT-5.4 is $13.20/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- GPT-5.4 adds Reasoning, Function calling, and Tool use in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-03-05 | 2025-09-01 |
| Context window | 1.05m | 128k |
| Parameters | — | 90B |
| Architecture | decoder only | - |
| License | Proprietary | Llama 3 Community |
| Openness | Proprietary | Open weights |
| Commercial use | Commercial use with conditions | Commercial use with conditions |
| Knowledge cutoff | 2025-08 | 2023-12 |
Pricing and availability
| Pricing attribute | GPT-5.4 | Llama 3.2 90B Instruct |
|---|---|---|
| Input price |
| $1.35/1M tokens |
| Output price |
| $1.80/1M tokens |
| Providers |
Capabilities
| Capability | GPT-5.4 | Llama 3.2 90B Instruct |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | Yes | No |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | Yes | Yes |
| Code execution | Yes | 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 differs most on reasoning mode: GPT-5.4, function calling: GPT-5.4, tool use: GPT-5.4, and code execution: GPT-5.4. Both models share vision, multimodal input, and structured outputs, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, GPT-5.4 lists tiered pricing: 0-272,000t is $2.50/1M input and $15/1M output; 272,000t+ is $5/1M input and $22.50/1M output, while Llama 3.2 90B Instruct lists $1.35/1M input and $1.80/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 3.2 90B Instruct lower by about $4.77 per million blended tokens. For tiered rows, this cheapest-track view can understate interactive or fast-lane spend, so compare the tier you will actually use. Availability is 3 providers versus 1, so concentration risk also matters.
Choose GPT-5.4 when coding workflow support, larger context windows, and broader provider choice are central to the workload. Choose Llama 3.2 90B Instruct when vision-heavy evaluation 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.
FAQ
Which has a larger context window, GPT-5.4 or Llama 3.2 90B Instruct?
GPT-5.4 supports 1.05m tokens, while Llama 3.2 90B Instruct 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, GPT-5.4 or Llama 3.2 90B Instruct?
GPT-5.4 lists tiered pricing: 0-272,000t is $2.50/1M input and $15/1M output; 272,000t+ is $5/1M input and $22.50/1M output. Llama 3.2 90B Instruct lists $1.35/1M input and $1.80/1M output tokens on the cheapest tracked provider. Compare the tier you will actually use; cheap async pricing can overstate savings for interactive workflows. Provider discounts or batch pricing can still change the final bill.
Is GPT-5.4 or Llama 3.2 90B Instruct open source?
GPT-5.4 is listed under Proprietary. Llama 3.2 90B Instruct is listed under Llama 3 Community. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for vision, GPT-5.4 or Llama 3.2 90B Instruct?
Both GPT-5.4 and Llama 3.2 90B Instruct expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, GPT-5.4 or Llama 3.2 90B Instruct?
Both GPT-5.4 and Llama 3.2 90B Instruct expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Where can I run GPT-5.4 and Llama 3.2 90B Instruct?
GPT-5.4 is available on OpenAI API, OpenRouter, and Vercel AI Gateway. Llama 3.2 90B Instruct is available on AWS Bedrock. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-06-04. Data sourced from public model cards and provider documentation.