MODEL PROOF
Llama 3.3 70B Instruct
BETTER VALUE OPTION
A stored alternative has an equal-or-higher measured score and an equal-or-lower price.
Serving precision differs between offers.
DeepSeek V4.1 Flash · Δ score 188.4 points · 9% lower measured price · $0.182 / 1M tokens
Gemma 3 4B is a further stored option with these losses: no tool use
- Independent LMArena score
- 1,274.1 ± 3.49 · 54,366 votes
- Context window
- 131.07K
- Maximum output
- 16.38K
- Input modalities
- text
- Output modalities
- text
- Published input price
- $0.135 / 1M tokens
- Published output price
- $0.400 / 1M tokens
- Pricing kind
- fixed
Inspect complete billing conditions and endpoint terms below.
Price from Novita: the cheapest offer that is serving, at standard delivery and at a declared precision that is not 4-bit (bf16), at its standard rate. The maker’s own precision is not known.
Cheaper right now: $0.155/M at DeepInfra — delivery tier (turbo) It does not pass the like-for-like test, so it never sets a rank.
Every price dimension · USD per million tokens
| Input | $0.135/M |
|---|---|
| Output | $0.400/M |
| Cached input | Unknown/M |
| Cache write | Unknown/M |
| Cache write 1h | Unknown/M |
| Reasoning | Unknown/M |
Who sells it
The same weights, different shops. Cheapest is not like-for-like when serving precision differs.
Headline cheapest is a lower precision. Like-for-like at the best declared precision is $0.135/M from Novita.
11 provider offers · rates, limits and conditions
Rates are USD per million tokens. Endpoint terms can differ even when the quoted price and precision match. A listed parameter is a provider declaration, not a task-success test.
| Seller | Input | Output | Precision | Uptime (1d) |
|---|---|---|---|---|
| DeepInfradeepinfra/turbo Endpoint terms
| $0.100 | $0.320 | fp8 | 98.28% |
| Novitanovita/bf16 Endpoint terms
| $0.135 | $0.400 | bf16 | 97.61% |
| AkashMLakashml/fp8 Endpoint terms
| $0.200 | $0.520 | fp8 | 99.23% |
| Parasailparasail/fp8 Endpoint terms
| $0.220 | $0.500 | fp8 | 99.66% |
| Cloudflarecloudflare/fp8 Endpoint terms
| $0.293 | $2.25 | fp8 | 98.72% |
| SambaNovasambanova-turbo Endpoint terms
| $0.450 | $0.900 | undeclared | 99.14% |
| Groqgroq Endpoint terms
| $0.590 | $0.790 | undeclared | 99.86% |
| CoreWeavecoreweave/fp16 Endpoint terms
| $0.710 | $0.710 | fp16 | 97.36% |
| Googlegoogle-vertex/us-central1 Endpoint terms
| $0.720 | $0.720 | undeclared | — |
| Googlegoogle-vertex Endpoint terms
| $0.720 | $0.720 | undeclared | — |
| Togethertogether Endpoint terms
| $1.04 | $1.04 | undeclared | 93.11% |
Independent scores
| LMArena Elo | 1274.1default |
|---|
LMArena Elo under CC BY 4.0. Absence of another board is not a score of zero.
Capability
| Context window | 131K |
|---|---|
| Max output | 16K |
| Input modes | text |
| Tool use | yes |
| Reasoning | no |
| Knowledge cutoff | 2023-12-31 |
| Open weights | Unknown |
Provenance
| Price source | openrouter.ai |
|---|---|
| Fetched | 2026-10-06 |
| Quality data | verified |
The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model...
Questions this page answers
What does Llama 3.3 70B Instruct cost?
$0.135/M in, $0.400/M out in this catalogue, as of the fetch date on this page. That is the API row, not a subscription.
Does Llama 3.3 70B Instruct have an independent quality score?
Llama 3.3 70B Instruct has an LMArena score in this catalogue.
What beats Llama 3.3 70B Instruct?
DeepSeek V4.1 Flash has an equal-or-higher measured score and an equal-or-lower price.
Does this page use Artificial Analysis scores for Llama 3.3 70B Instruct?
No. Artificial Analysis figures are not published here. Quality on this page is LMArena Elo where a score exists; otherwise the row is unrated.
Is the cheapest Llama 3.3 70B Instruct endpoint the same product?
Headline cheapest is a lower precision. Like-for-like at the best declared precision is $0.135/M from Novita.
MODEL MONUMENT
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The verdict as one SVG, for a README or a docs page. It states this model's dominance status at the balanced workload on the LMArena lens, with the date it was computed, and it is rebuilt with the catalogue — so it changes when the verdict changes, including to one you would rather it did not.
[](https://undominated.ai/models/meta-llama__llama-3.3-70b-instruct/)<a href="https://undominated.ai/models/meta-llama__llama-3.3-70b-instruct/"><img src="https://undominated.ai/badge/meta-llama__llama-3.3-70b-instruct.svg" alt="Llama 3.3 70B Instruct — Undominated.ai dominance verdict" height="36"></a>Direct file: https://undominated.ai/badge/meta-llama__llama-3.3-70b-instruct.svg — a static SVG, written by scripts/build-badges.mjs on every build, so the copy you embed is never
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